![[Stable]](figures/lifecycle-stable.svg)
Usage
component(
object,
name = c("cov_type", "subject_var", "n_theta", "n_subjects", "n_timepoints", "n_obs",
"beta_vcov", "beta_vcov_complete", "varcor", "formula", "dataset", "n_groups",
"reml", "convergence", "evaluations", "method", "optimizer", "conv_message", "call",
"theta_est", "beta_est", "beta_est_complete", "beta_aliased", "x_matrix", "y_vector",
"neg_log_lik", "jac_list", "theta_vcov", "full_frame", "xlev", "contrasts")
)Details
Available component() names are as follows:
call: low-level function call which generated the model.formula: model formula.dataset: data set name.cov_type: covariance structure type.n_theta: number of parameters.n_subjects: number of subjects.n_timepoints: number of modeled time points.n_obs: total number of observations.reml: was REML used (ML was used ifFALSE).neg_log_lik: negative log likelihood.convergence: convergence code from optimizer.conv_message: message accompanying the convergence code.evaluations: number of function evaluations for optimization.method: Adjustment method which was used (formmrmobjects), otherwiseNULL(formmrm_tmbobjects).beta_vcov: estimated variance-covariance matrix of coefficients (excluding aliased coefficients). When Kenward-Roger/Empirical adjusted coefficients covariance matrix is used, the adjusted covariance matrix is returned (to still obtain the original asymptotic covariance matrix useobject$beta_vcov).beta_vcov_complete: estimated variance-covariance matrix including aliased coefficients with entries set toNA.varcor: estimated covariance matrix for residuals. If there are multiple groups, a named list of estimated covariance matrices for residuals will be returned. The names are the group levels.theta_est: estimated variance parameters.beta_est: estimated coefficients (excluding aliased coefficients).beta_est_complete: estimated coefficients including aliased coefficients set toNA.beta_aliased: whether each coefficient was aliased (i.e. cannot be estimated) or not.theta_vcov: estimated variance-covariance matrix of variance parameters.x_matrix: design matrix used (excluding aliased columns).xlev: a named list of character vectors giving the full set of levels to be assumed for each factor.contrasts: a list of contrasts used for each factor.y_vector: response vector used.jac_list: Jacobian, seeh_jac_list()for details.full_frame:data.framewithnrows containing all variables needed in the model.
Examples
fit <- mmrm(
formula = FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID),
data = fev_data
)
# Get all available components.
component(fit)
#> $cov_type
#> [1] "us"
#>
#> $subject_var
#> [1] "USUBJID"
#>
#> $n_theta
#> [1] 10
#>
#> $n_subjects
#> [1] 197
#>
#> $n_timepoints
#> [1] 4
#>
#> $n_obs
#> [1] 537
#>
#> $beta_vcov
#> (Intercept) RACEBlack or African American
#> (Intercept) 0.7859971 -0.226212328
#> RACEBlack or African American -0.2262123 0.389969478
#> RACEWhite -0.1771113 0.181466304
#> SEXFemale -0.1684152 0.031537926
#> ARMCDTRT -0.5674809 0.028374129
#> AVISITVIS2 -0.4227565 0.002972514
#> AVISITVIS3 -0.5231223 0.010825469
#> AVISITVIS4 -0.4406442 0.002205681
#> ARMCDTRT:AVISITVIS2 0.4225282 0.005382569
#> ARMCDTRT:AVISITVIS3 0.5218971 0.011420575
#> ARMCDTRT:AVISITVIS4 0.4489247 -0.012589283
#> RACEWhite SEXFemale ARMCDTRT
#> (Intercept) -0.177111308 -0.168415217 -0.567480906
#> RACEBlack or African American 0.181466304 0.031537926 0.028374129
#> RACEWhite 0.443035801 0.023364777 -0.042968995
#> SEXFemale 0.023364777 0.282971189 0.001814594
#> ARMCDTRT -0.042968995 0.001814594 1.153791725
#> AVISITVIS2 -0.003149280 0.006471853 0.419528600
#> AVISITVIS3 -0.002952986 0.006771404 0.517277529
#> AVISITVIS4 -0.008230720 0.004088901 0.440653554
#> ARMCDTRT:AVISITVIS2 0.013485683 -0.016801299 -0.845758354
#> ARMCDTRT:AVISITVIS3 0.006720617 -0.024696304 -1.044355829
#> ARMCDTRT:AVISITVIS4 0.002967665 -0.009038640 -0.877606881
#> AVISITVIS2 AVISITVIS3 AVISITVIS4
#> (Intercept) -0.422756455 -0.523122299 -0.440644229
#> RACEBlack or African American 0.002972514 0.010825469 0.002205681
#> RACEWhite -0.003149280 -0.002952986 -0.008230720
#> SEXFemale 0.006471853 0.006771404 0.004088901
#> ARMCDTRT 0.419528600 0.517277529 0.440653554
#> AVISITVIS2 0.642749706 0.399048940 0.368340113
#> AVISITVIS3 0.399048940 0.676823960 0.401800094
#> AVISITVIS4 0.368340113 0.401800094 1.723478787
#> ARMCDTRT:AVISITVIS2 -0.643020114 -0.399203255 -0.368624024
#> ARMCDTRT:AVISITVIS3 -0.399238901 -0.676484876 -0.401792995
#> ARMCDTRT:AVISITVIS4 -0.368506585 -0.402167824 -1.723586879
#> ARMCDTRT:AVISITVIS2 ARMCDTRT:AVISITVIS3
#> (Intercept) 0.422528163 0.521897062
#> RACEBlack or African American 0.005382569 0.011420575
#> RACEWhite 0.013485683 0.006720617
#> SEXFemale -0.016801299 -0.024696304
#> ARMCDTRT -0.845758354 -1.044355829
#> AVISITVIS2 -0.643020114 -0.399238901
#> AVISITVIS3 -0.399203255 -0.676484876
#> AVISITVIS4 -0.368624024 -0.401792995
#> ARMCDTRT:AVISITVIS2 1.275359305 0.805849821
#> ARMCDTRT:AVISITVIS3 0.805849821 1.410501907
#> ARMCDTRT:AVISITVIS4 0.728711516 0.796418986
#> ARMCDTRT:AVISITVIS4
#> (Intercept) 0.448924745
#> RACEBlack or African American -0.012589283
#> RACEWhite 0.002967665
#> SEXFemale -0.009038640
#> ARMCDTRT -0.877606881
#> AVISITVIS2 -0.368506585
#> AVISITVIS3 -0.402167824
#> AVISITVIS4 -1.723586879
#> ARMCDTRT:AVISITVIS2 0.728711516
#> ARMCDTRT:AVISITVIS3 0.796418986
#> ARMCDTRT:AVISITVIS4 3.425654435
#>
#> $beta_vcov_complete
#> (Intercept) RACEBlack or African American
#> (Intercept) 0.7859971 -0.226212328
#> RACEBlack or African American -0.2262123 0.389969478
#> RACEWhite -0.1771113 0.181466304
#> SEXFemale -0.1684152 0.031537926
#> ARMCDTRT -0.5674809 0.028374129
#> AVISITVIS2 -0.4227565 0.002972514
#> AVISITVIS3 -0.5231223 0.010825469
#> AVISITVIS4 -0.4406442 0.002205681
#> ARMCDTRT:AVISITVIS2 0.4225282 0.005382569
#> ARMCDTRT:AVISITVIS3 0.5218971 0.011420575
#> ARMCDTRT:AVISITVIS4 0.4489247 -0.012589283
#> RACEWhite SEXFemale ARMCDTRT
#> (Intercept) -0.177111308 -0.168415217 -0.567480906
#> RACEBlack or African American 0.181466304 0.031537926 0.028374129
#> RACEWhite 0.443035801 0.023364777 -0.042968995
#> SEXFemale 0.023364777 0.282971189 0.001814594
#> ARMCDTRT -0.042968995 0.001814594 1.153791725
#> AVISITVIS2 -0.003149280 0.006471853 0.419528600
#> AVISITVIS3 -0.002952986 0.006771404 0.517277529
#> AVISITVIS4 -0.008230720 0.004088901 0.440653554
#> ARMCDTRT:AVISITVIS2 0.013485683 -0.016801299 -0.845758354
#> ARMCDTRT:AVISITVIS3 0.006720617 -0.024696304 -1.044355829
#> ARMCDTRT:AVISITVIS4 0.002967665 -0.009038640 -0.877606881
#> AVISITVIS2 AVISITVIS3 AVISITVIS4
#> (Intercept) -0.422756455 -0.523122299 -0.440644229
#> RACEBlack or African American 0.002972514 0.010825469 0.002205681
#> RACEWhite -0.003149280 -0.002952986 -0.008230720
#> SEXFemale 0.006471853 0.006771404 0.004088901
#> ARMCDTRT 0.419528600 0.517277529 0.440653554
#> AVISITVIS2 0.642749706 0.399048940 0.368340113
#> AVISITVIS3 0.399048940 0.676823960 0.401800094
#> AVISITVIS4 0.368340113 0.401800094 1.723478787
#> ARMCDTRT:AVISITVIS2 -0.643020114 -0.399203255 -0.368624024
#> ARMCDTRT:AVISITVIS3 -0.399238901 -0.676484876 -0.401792995
#> ARMCDTRT:AVISITVIS4 -0.368506585 -0.402167824 -1.723586879
#> ARMCDTRT:AVISITVIS2 ARMCDTRT:AVISITVIS3
#> (Intercept) 0.422528163 0.521897062
#> RACEBlack or African American 0.005382569 0.011420575
#> RACEWhite 0.013485683 0.006720617
#> SEXFemale -0.016801299 -0.024696304
#> ARMCDTRT -0.845758354 -1.044355829
#> AVISITVIS2 -0.643020114 -0.399238901
#> AVISITVIS3 -0.399203255 -0.676484876
#> AVISITVIS4 -0.368624024 -0.401792995
#> ARMCDTRT:AVISITVIS2 1.275359305 0.805849821
#> ARMCDTRT:AVISITVIS3 0.805849821 1.410501907
#> ARMCDTRT:AVISITVIS4 0.728711516 0.796418986
#> ARMCDTRT:AVISITVIS4
#> (Intercept) 0.448924745
#> RACEBlack or African American -0.012589283
#> RACEWhite 0.002967665
#> SEXFemale -0.009038640
#> ARMCDTRT -0.877606881
#> AVISITVIS2 -0.368506585
#> AVISITVIS3 -0.402167824
#> AVISITVIS4 -1.723586879
#> ARMCDTRT:AVISITVIS2 0.728711516
#> ARMCDTRT:AVISITVIS3 0.796418986
#> ARMCDTRT:AVISITVIS4 3.425654435
#>
#> $varcor
#> VIS1 VIS2 VIS3 VIS4
#> VIS1 40.553664 14.396045 4.9747288 13.3866534
#> VIS2 14.396045 26.571483 2.7854661 7.4744790
#> VIS3 4.974729 2.785466 14.8978517 0.9082111
#> VIS4 13.386653 7.474479 0.9082111 95.5568420
#>
#> $formula
#> [1] "FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID)"
#>
#> $dataset
#> fev_data
#>
#> $n_groups
#> [1] 1
#>
#> $reml
#> [1] TRUE
#>
#> $convergence
#> [1] 0
#>
#> $evaluations
#> function gradient
#> 15 15
#>
#> $method
#> [1] "Satterthwaite"
#>
#> $optimizer
#> [1] "L-BFGS-B"
#>
#> $conv_message
#> [1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH"
#>
#> $call
#> mmrm(formula = FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT |
#> USUBJID), data = fev_data)
#>
#> $theta_est
#> [1] 1.85131306 1.53312022 1.32799829 2.25400062 0.48798054 0.20701987
#> [7] 0.05832020 0.22067693 0.06169127 -0.02401589
#>
#> $beta_est
#> (Intercept) RACEBlack or African American
#> 30.77747548 1.53049977
#> RACEWhite SEXFemale
#> 5.64356535 0.32606192
#> ARMCDTRT AVISITVIS2
#> 3.77423004 4.83958845
#> AVISITVIS3 AVISITVIS4
#> 10.34211288 15.05389826
#> ARMCDTRT:AVISITVIS2 ARMCDTRT:AVISITVIS3
#> -0.04192625 -0.69368537
#> ARMCDTRT:AVISITVIS4
#> 0.62422703
#>
#> $beta_est_complete
#> (Intercept) RACEBlack or African American
#> 30.77747548 1.53049977
#> RACEWhite SEXFemale
#> 5.64356535 0.32606192
#> ARMCDTRT AVISITVIS2
#> 3.77423004 4.83958845
#> AVISITVIS3 AVISITVIS4
#> 10.34211288 15.05389826
#> ARMCDTRT:AVISITVIS2 ARMCDTRT:AVISITVIS3
#> -0.04192625 -0.69368537
#> ARMCDTRT:AVISITVIS4
#> 0.62422703
#>
#> $beta_aliased
#> (Intercept) RACEBlack or African American
#> FALSE FALSE
#> RACEWhite SEXFemale
#> FALSE FALSE
#> ARMCDTRT AVISITVIS2
#> FALSE FALSE
#> AVISITVIS3 AVISITVIS4
#> FALSE FALSE
#> ARMCDTRT:AVISITVIS2 ARMCDTRT:AVISITVIS3
#> FALSE FALSE
#> ARMCDTRT:AVISITVIS4
#> FALSE
#>
#> $x_matrix
#> (Intercept) RACEBlack or African American RACEWhite SEXFemale ARMCDTRT
#> 2 1 1 0 1 1
#> 4 1 1 0 1 1
#> 6 1 0 0 0 0
#> 7 1 0 0 0 0
#> 8 1 0 0 0 0
#> 10 1 1 0 1 0
#> 12 1 1 0 1 0
#> 13 1 0 0 1 1
#> 14 1 0 0 1 1
#> 16 1 0 0 1 1
#> 17 1 1 0 0 0
#> 19 1 1 0 0 0
#> 20 1 1 0 0 0
#> 23 1 1 0 0 0
#> 25 1 0 0 1 0
#> 26 1 0 0 1 0
#> 28 1 0 0 1 0
#> 29 1 1 0 0 0
#> 30 1 1 0 0 0
#> 31 1 1 0 0 0
#> 32 1 1 0 0 0
#> 33 1 0 1 0 1
#> 34 1 0 1 0 1
#> 36 1 0 1 0 1
#> 39 1 1 0 1 0
#> 41 1 0 0 1 1
#> 42 1 0 0 1 1
#> 43 1 0 0 1 1
#> 44 1 0 0 1 1
#> 45 1 0 0 0 0
#> 46 1 0 0 0 0
#> 47 1 0 0 0 0
#> 51 1 0 1 0 1
#> 52 1 0 1 0 1
#> 55 1 1 0 0 0
#> 59 1 0 0 0 0
#> 60 1 0 0 0 0
#> 62 1 0 0 1 0
#> 64 1 0 0 1 0
#> 65 1 0 1 1 0
#> 68 1 0 1 1 0
#> 69 1 0 0 0 1
#> 70 1 0 0 0 1
#> 72 1 0 0 0 1
#> 73 1 0 0 0 1
#> 74 1 0 0 0 1
#> 75 1 0 0 0 1
#> 76 1 0 0 0 1
#> 78 1 0 1 1 1
#> 79 1 0 1 1 1
#> 82 1 0 1 0 1
#> 83 1 0 1 0 1
#> 84 1 0 1 0 1
#> 85 1 0 1 0 1
#> 86 1 0 1 0 1
#> 87 1 0 1 0 1
#> 88 1 0 1 0 1
#> 89 1 1 0 1 0
#> 90 1 1 0 1 0
#> 91 1 1 0 1 0
#> 93 1 0 1 1 1
#> 94 1 0 1 1 1
#> 95 1 0 1 1 1
#> 96 1 0 1 1 1
#> 97 1 0 1 1 1
#> 98 1 0 1 1 1
#> 99 1 0 1 1 1
#> 100 1 0 1 1 1
#> 101 1 0 1 1 1
#> 102 1 0 1 1 1
#> 103 1 0 1 1 1
#> 104 1 0 1 1 1
#> 105 1 1 0 1 1
#> 107 1 1 0 1 1
#> 108 1 1 0 1 1
#> 109 1 1 0 0 1
#> 110 1 1 0 0 1
#> 111 1 1 0 0 1
#> 112 1 1 0 0 1
#> 113 1 1 0 0 1
#> 114 1 1 0 0 1
#> 116 1 1 0 0 1
#> 117 1 0 0 1 1
#> 118 1 0 0 1 1
#> 119 1 0 0 1 1
#> 120 1 0 0 1 1
#> 121 1 0 0 1 0
#> 123 1 0 0 1 0
#> 125 1 1 0 0 1
#> 128 1 1 0 0 1
#> 129 1 1 0 0 1
#> 130 1 1 0 0 1
#> 132 1 1 0 0 1
#> 133 1 0 0 1 0
#> 134 1 0 0 1 0
#> 135 1 0 0 1 0
#> 136 1 0 0 1 0
#> 137 1 1 0 1 1
#> 138 1 1 0 1 1
#> 140 1 1 0 1 1
#> 142 1 0 0 1 1
#> 144 1 0 0 1 1
#> 145 1 0 1 1 0
#> 146 1 0 1 1 0
#> 147 1 0 1 1 0
#> 148 1 0 1 1 0
#> 149 1 0 0 1 0
#> 151 1 0 0 1 0
#> 153 1 0 0 1 0
#> 155 1 0 0 1 0
#> 156 1 0 0 1 0
#> 157 1 1 0 0 0
#> 158 1 1 0 0 0
#> 159 1 1 0 0 0
#> 162 1 1 0 0 0
#> 163 1 1 0 0 0
#> 164 1 1 0 0 0
#> 165 1 1 0 0 0
#> 168 1 1 0 0 0
#> 169 1 1 0 1 1
#> 170 1 1 0 1 1
#> 171 1 1 0 1 1
#> 172 1 1 0 1 1
#> 173 1 1 0 0 1
#> 177 1 0 0 1 0
#> 178 1 0 0 1 0
#> 179 1 0 0 1 0
#> 180 1 0 0 1 0
#> 181 1 0 0 0 0
#> 182 1 0 0 0 0
#> 183 1 0 0 0 0
#> 185 1 0 0 0 1
#> 186 1 0 0 0 1
#> 187 1 0 0 0 1
#> 190 1 1 0 0 0
#> 191 1 1 0 0 0
#> 193 1 0 1 1 0
#> 194 1 0 1 1 0
#> 195 1 0 1 1 0
#> 197 1 0 0 1 1
#> 198 1 0 0 1 1
#> 199 1 0 0 1 1
#> 201 1 1 0 1 1
#> 202 1 1 0 1 1
#> 204 1 1 0 1 1
#> 206 1 1 0 1 1
#> 208 1 1 0 1 1
#> 209 1 0 1 0 0
#> 210 1 0 1 0 0
#> 217 1 0 0 0 1
#> 218 1 0 0 0 1
#> 219 1 0 0 0 1
#> 221 1 1 0 0 0
#> 224 1 1 0 0 0
#> 226 1 1 0 0 1
#> 227 1 1 0 0 1
#> 228 1 1 0 0 1
#> 230 1 0 1 1 1
#> 231 1 0 1 1 1
#> 233 1 0 1 1 1
#> 235 1 0 1 1 1
#> 236 1 0 1 1 1
#> 237 1 1 0 1 1
#> 238 1 1 0 1 1
#> 239 1 1 0 1 1
#> 240 1 1 0 1 1
#> 241 1 0 0 0 1
#> 242 1 0 0 0 1
#> 244 1 0 0 0 1
#> 246 1 0 0 1 0
#> 250 1 0 1 1 0
#> 251 1 0 1 1 0
#> 252 1 0 1 1 0
#> 253 1 1 0 1 0
#> 254 1 1 0 1 0
#> 256 1 1 0 1 0
#> 257 1 0 0 1 1
#> 258 1 0 0 1 1
#> 259 1 0 0 1 1
#> 260 1 0 0 1 1
#> 261 1 0 0 0 1
#> 262 1 0 0 0 1
#> 263 1 0 0 0 1
#> 264 1 0 0 0 1
#> 265 1 0 1 1 1
#> 266 1 0 1 1 1
#> 267 1 0 1 1 1
#> 268 1 0 1 1 1
#> 269 1 0 1 1 1
#> 270 1 0 1 1 1
#> 273 1 1 0 0 0
#> 274 1 1 0 0 0
#> 275 1 1 0 0 0
#> 276 1 1 0 0 0
#> 277 1 1 0 0 0
#> 278 1 1 0 0 0
#> 280 1 1 0 0 0
#> 281 1 0 0 0 1
#> 282 1 0 0 0 1
#> 283 1 0 0 0 1
#> 284 1 0 0 0 1
#> 285 1 0 0 1 1
#> 286 1 0 0 1 1
#> 287 1 0 0 1 1
#> 291 1 0 1 0 0
#> 292 1 0 1 0 0
#> 293 1 0 1 1 0
#> 295 1 0 1 1 0
#> 296 1 0 1 1 0
#> 298 1 0 1 0 0
#> 299 1 0 1 0 0
#> 300 1 0 1 0 0
#> 301 1 0 1 0 1
#> 304 1 0 1 0 1
#> 305 1 0 0 0 1
#> 306 1 0 0 0 1
#> 307 1 0 0 0 1
#> 308 1 0 0 0 1
#> 310 1 0 1 1 1
#> 311 1 0 1 1 1
#> 312 1 0 1 1 1
#> 316 1 0 0 1 0
#> 317 1 0 0 0 1
#> 318 1 0 0 0 1
#> 319 1 0 0 0 1
#> 322 1 0 1 0 0
#> 323 1 0 1 0 0
#> 324 1 0 1 0 0
#> 325 1 1 0 1 0
#> 327 1 1 0 1 0
#> 328 1 1 0 1 0
#> 329 1 0 1 0 1
#> 330 1 0 1 0 1
#> 331 1 0 1 0 1
#> 332 1 0 1 0 1
#> 336 1 0 0 1 0
#> 339 1 0 0 1 0
#> 340 1 0 0 1 0
#> 341 1 1 0 1 1
#> 342 1 1 0 1 1
#> 343 1 1 0 1 1
#> 344 1 1 0 1 1
#> 345 1 0 1 0 0
#> 347 1 0 1 0 0
#> 349 1 1 0 1 0
#> 351 1 1 0 1 0
#> 352 1 1 0 1 0
#> 353 1 1 0 0 0
#> 354 1 1 0 0 0
#> 355 1 1 0 0 0
#> 356 1 1 0 0 0
#> 357 1 0 0 0 0
#> 363 1 0 1 1 1
#> 364 1 0 1 1 1
#> 365 1 0 1 1 1
#> 367 1 0 1 1 1
#> 368 1 0 1 1 1
#> 370 1 1 0 0 0
#> 371 1 1 0 0 0
#> 372 1 1 0 0 0
#> 373 1 0 0 1 0
#> 375 1 0 0 1 0
#> 376 1 0 0 1 0
#> 378 1 0 0 1 0
#> 379 1 0 0 1 0
#> 381 1 1 0 1 0
#> 382 1 1 0 1 0
#> 384 1 1 0 1 0
#> 385 1 0 1 0 1
#> 386 1 0 1 0 1
#> 388 1 0 1 0 1
#> 389 1 0 0 0 0
#> 390 1 0 0 0 0
#> 391 1 0 0 0 0
#> 392 1 0 0 0 0
#> 394 1 1 0 0 0
#> 397 1 1 0 1 0
#> 398 1 1 0 1 0
#> 399 1 1 0 1 0
#> 402 1 0 1 0 1
#> 403 1 0 1 0 1
#> 405 1 0 0 1 0
#> 406 1 0 0 1 0
#> 407 1 0 0 1 0
#> 408 1 0 0 1 0
#> 409 1 0 0 1 0
#> 410 1 0 0 1 0
#> 411 1 0 0 1 0
#> 413 1 1 0 1 0
#> 415 1 1 0 1 0
#> 416 1 1 0 1 0
#> 418 1 1 0 1 1
#> 419 1 1 0 1 1
#> 421 1 0 0 1 1
#> 422 1 0 0 1 1
#> 423 1 0 0 1 1
#> 424 1 0 0 1 1
#> 427 1 0 1 1 0
#> 428 1 0 1 1 0
#> 429 1 0 1 0 1
#> 430 1 0 1 0 1
#> 431 1 0 1 0 1
#> 432 1 0 1 0 1
#> 434 1 1 0 1 0
#> 435 1 1 0 1 0
#> 436 1 1 0 1 0
#> 438 1 0 0 0 1
#> 439 1 0 0 0 1
#> 444 1 0 1 1 0
#> 445 1 1 0 1 0
#> 447 1 1 0 1 0
#> 449 1 0 0 0 0
#> 450 1 0 0 0 0
#> 451 1 0 0 0 0
#> 453 1 1 0 0 0
#> 454 1 1 0 0 0
#> 455 1 1 0 0 0
#> 456 1 1 0 0 0
#> 457 1 0 0 1 0
#> 458 1 0 0 1 0
#> 459 1 0 0 1 0
#> 461 1 1 0 0 1
#> 463 1 1 0 0 1
#> 464 1 1 0 0 1
#> 465 1 1 0 0 0
#> 469 1 0 0 1 0
#> 470 1 0 0 1 0
#> 471 1 0 0 1 0
#> 473 1 0 1 0 1
#> 474 1 0 1 0 1
#> 477 1 0 0 1 0
#> 484 1 1 0 0 1
#> 487 1 0 0 1 0
#> 489 1 0 1 1 0
#> 490 1 0 1 1 0
#> 491 1 0 1 1 0
#> 494 1 0 0 1 1
#> 495 1 0 0 1 1
#> 496 1 0 0 1 1
#> 497 1 0 1 0 0
#> 498 1 0 1 0 0
#> 499 1 0 1 0 0
#> 501 1 0 0 0 1
#> 502 1 0 0 0 1
#> 504 1 0 0 0 1
#> 505 1 1 0 1 1
#> 508 1 1 0 1 1
#> 509 1 0 0 1 1
#> 510 1 0 0 1 1
#> 511 1 0 0 1 1
#> 512 1 0 0 1 1
#> 513 1 0 1 0 1
#> 518 1 0 1 0 0
#> 519 1 0 1 0 0
#> 521 1 0 0 1 0
#> 522 1 0 0 1 0
#> 523 1 0 0 1 0
#> 524 1 0 0 1 0
#> 526 1 0 0 0 0
#> 527 1 0 0 0 0
#> 528 1 0 0 0 0
#> 530 1 0 1 0 0
#> 531 1 0 1 0 0
#> 532 1 0 1 0 0
#> 534 1 1 0 0 0
#> 535 1 1 0 0 0
#> 536 1 1 0 0 0
#> 537 1 1 0 0 0
#> 538 1 1 0 0 0
#> 539 1 1 0 0 0
#> 540 1 1 0 0 0
#> 541 1 0 1 1 1
#> 544 1 0 1 1 1
#> 545 1 0 0 1 1
#> 546 1 0 0 1 1
#> 547 1 0 0 1 1
#> 548 1 0 0 1 1
#> 549 1 0 0 0 1
#> 550 1 0 0 0 1
#> 551 1 0 0 0 1
#> 555 1 0 0 1 1
#> 556 1 0 0 1 1
#> 557 1 1 0 1 0
#> 558 1 1 0 1 0
#> 560 1 1 0 1 0
#> 562 1 0 1 0 1
#> 564 1 0 1 0 1
#> 569 1 1 0 1 1
#> 570 1 1 0 1 1
#> 572 1 1 0 1 1
#> 573 1 0 0 1 0
#> 574 1 0 0 1 0
#> 575 1 0 0 1 0
#> 576 1 0 0 1 0
#> 577 1 1 0 0 0
#> 578 1 1 0 0 0
#> 579 1 1 0 0 0
#> 582 1 0 0 1 1
#> 583 1 0 0 1 1
#> 584 1 0 0 1 1
#> 585 1 0 0 1 0
#> 586 1 0 0 1 0
#> 587 1 0 0 1 0
#> 590 1 1 0 0 1
#> 591 1 1 0 0 1
#> 593 1 0 0 1 0
#> 594 1 0 0 1 0
#> 595 1 0 0 1 0
#> 596 1 0 0 1 0
#> 599 1 0 1 0 0
#> 600 1 0 1 0 0
#> 601 1 0 0 1 0
#> 602 1 0 0 1 0
#> 604 1 0 0 1 0
#> 606 1 0 0 1 1
#> 608 1 0 0 1 1
#> 609 1 1 0 0 0
#> 610 1 1 0 0 0
#> 611 1 1 0 0 0
#> 612 1 1 0 0 0
#> 613 1 1 0 1 0
#> 614 1 1 0 1 0
#> 616 1 1 0 1 0
#> 617 1 0 0 0 1
#> 619 1 0 0 0 1
#> 620 1 0 0 0 1
#> 621 1 0 1 0 0
#> 622 1 0 1 0 0
#> 623 1 0 1 0 0
#> 624 1 0 1 0 0
#> 625 1 1 0 0 1
#> 628 1 1 0 0 1
#> 630 1 1 0 0 1
#> 631 1 1 0 0 1
#> 632 1 1 0 0 1
#> 633 1 0 0 1 1
#> 634 1 0 0 1 1
#> 638 1 0 0 0 1
#> 639 1 0 0 0 1
#> 640 1 0 0 0 1
#> 642 1 1 0 1 0
#> 645 1 0 0 0 0
#> 648 1 0 0 0 0
#> 650 1 0 1 0 0
#> 652 1 0 1 0 0
#> 654 1 1 0 1 0
#> 655 1 1 0 1 0
#> 656 1 1 0 1 0
#> 657 1 0 1 1 1
#> 661 1 0 0 0 1
#> 665 1 1 0 0 0
#> 666 1 1 0 0 0
#> 668 1 1 0 0 0
#> 669 1 1 0 1 0
#> 670 1 1 0 1 0
#> 671 1 1 0 1 0
#> 673 1 0 1 1 0
#> 674 1 0 1 1 0
#> 678 1 0 1 1 1
#> 679 1 0 1 1 1
#> 680 1 0 1 1 1
#> 682 1 0 0 1 0
#> 684 1 0 0 1 0
#> 685 1 0 0 1 1
#> 686 1 0 0 1 1
#> 687 1 0 0 1 1
#> 689 1 0 1 1 1
#> 690 1 0 1 1 1
#> 691 1 0 1 1 1
#> 693 1 1 0 1 1
#> 694 1 1 0 1 1
#> 695 1 1 0 1 1
#> 697 1 1 0 1 0
#> 698 1 1 0 1 0
#> 700 1 1 0 1 0
#> 701 1 1 0 0 1
#> 702 1 1 0 0 1
#> 704 1 1 0 0 1
#> 707 1 1 0 0 0
#> 709 1 1 0 0 0
#> 712 1 1 0 0 0
#> 713 1 0 1 0 1
#> 715 1 0 1 0 1
#> 716 1 0 1 0 1
#> 717 1 0 0 0 0
#> 718 1 0 0 0 0
#> 719 1 0 0 0 0
#> 721 1 0 0 1 0
#> 723 1 0 0 1 0
#> 724 1 0 0 1 0
#> 727 1 1 0 1 1
#> 728 1 1 0 1 1
#> 729 1 1 0 1 1
#> 730 1 1 0 1 1
#> 734 1 0 1 1 1
#> 736 1 0 1 1 1
#> 738 1 1 0 1 0
#> 739 1 1 0 1 0
#> 740 1 1 0 1 0
#> 741 1 0 1 0 0
#> 742 1 0 1 0 0
#> 744 1 0 1 0 0
#> 745 1 1 0 1 0
#> 749 1 1 0 1 0
#> 751 1 1 0 1 0
#> 753 1 0 0 1 1
#> 754 1 0 0 1 1
#> 755 1 0 0 1 1
#> 757 1 1 0 1 1
#> 758 1 1 0 1 1
#> 759 1 1 0 1 1
#> 760 1 1 0 1 1
#> 761 1 0 1 0 1
#> 764 1 0 1 0 1
#> 765 1 0 1 1 1
#> 766 1 0 1 1 1
#> 767 1 0 1 1 1
#> 768 1 0 1 1 1
#> 770 1 0 0 0 0
#> 771 1 0 0 0 0
#> 772 1 0 0 0 0
#> 773 1 1 0 0 0
#> 774 1 1 0 0 0
#> 775 1 1 0 0 0
#> 776 1 1 0 0 0
#> 778 1 0 1 1 1
#> 779 1 0 1 1 1
#> 781 1 0 0 0 0
#> 782 1 0 0 0 0
#> 784 1 0 0 0 0
#> 788 1 1 0 0 0
#> 789 1 1 0 0 1
#> 790 1 1 0 0 1
#> 792 1 1 0 0 1
#> 797 1 1 0 0 0
#> 798 1 1 0 0 0
#> 800 1 1 0 0 0
#> AVISITVIS2 AVISITVIS3 AVISITVIS4 ARMCDTRT:AVISITVIS2 ARMCDTRT:AVISITVIS3
#> 2 1 0 0 1 0
#> 4 0 0 1 0 0
#> 6 1 0 0 0 0
#> 7 0 1 0 0 0
#> 8 0 0 1 0 0
#> 10 1 0 0 0 0
#> 12 0 0 1 0 0
#> 13 0 0 0 0 0
#> 14 1 0 0 1 0
#> 16 0 0 1 0 0
#> 17 0 0 0 0 0
#> 19 0 1 0 0 0
#> 20 0 0 1 0 0
#> 23 0 1 0 0 0
#> 25 0 0 0 0 0
#> 26 1 0 0 0 0
#> 28 0 0 1 0 0
#> 29 0 0 0 0 0
#> 30 1 0 0 0 0
#> 31 0 1 0 0 0
#> 32 0 0 1 0 0
#> 33 0 0 0 0 0
#> 34 1 0 0 1 0
#> 36 0 0 1 0 0
#> 39 0 1 0 0 0
#> 41 0 0 0 0 0
#> 42 1 0 0 1 0
#> 43 0 1 0 0 1
#> 44 0 0 1 0 0
#> 45 0 0 0 0 0
#> 46 1 0 0 0 0
#> 47 0 1 0 0 0
#> 51 0 1 0 0 1
#> 52 0 0 1 0 0
#> 55 0 1 0 0 0
#> 59 0 1 0 0 0
#> 60 0 0 1 0 0
#> 62 1 0 0 0 0
#> 64 0 0 1 0 0
#> 65 0 0 0 0 0
#> 68 0 0 1 0 0
#> 69 0 0 0 0 0
#> 70 1 0 0 1 0
#> 72 0 0 1 0 0
#> 73 0 0 0 0 0
#> 74 1 0 0 1 0
#> 75 0 1 0 0 1
#> 76 0 0 1 0 0
#> 78 1 0 0 1 0
#> 79 0 1 0 0 1
#> 82 1 0 0 1 0
#> 83 0 1 0 0 1
#> 84 0 0 1 0 0
#> 85 0 0 0 0 0
#> 86 1 0 0 1 0
#> 87 0 1 0 0 1
#> 88 0 0 1 0 0
#> 89 0 0 0 0 0
#> 90 1 0 0 0 0
#> 91 0 1 0 0 0
#> 93 0 0 0 0 0
#> 94 1 0 0 1 0
#> 95 0 1 0 0 1
#> 96 0 0 1 0 0
#> 97 0 0 0 0 0
#> 98 1 0 0 1 0
#> 99 0 1 0 0 1
#> 100 0 0 1 0 0
#> 101 0 0 0 0 0
#> 102 1 0 0 1 0
#> 103 0 1 0 0 1
#> 104 0 0 1 0 0
#> 105 0 0 0 0 0
#> 107 0 1 0 0 1
#> 108 0 0 1 0 0
#> 109 0 0 0 0 0
#> 110 1 0 0 1 0
#> 111 0 1 0 0 1
#> 112 0 0 1 0 0
#> 113 0 0 0 0 0
#> 114 1 0 0 1 0
#> 116 0 0 1 0 0
#> 117 0 0 0 0 0
#> 118 1 0 0 1 0
#> 119 0 1 0 0 1
#> 120 0 0 1 0 0
#> 121 0 0 0 0 0
#> 123 0 1 0 0 0
#> 125 0 0 0 0 0
#> 128 0 0 1 0 0
#> 129 0 0 0 0 0
#> 130 1 0 0 1 0
#> 132 0 0 1 0 0
#> 133 0 0 0 0 0
#> 134 1 0 0 0 0
#> 135 0 1 0 0 0
#> 136 0 0 1 0 0
#> 137 0 0 0 0 0
#> 138 1 0 0 1 0
#> 140 0 0 1 0 0
#> 142 1 0 0 1 0
#> 144 0 0 1 0 0
#> 145 0 0 0 0 0
#> 146 1 0 0 0 0
#> 147 0 1 0 0 0
#> 148 0 0 1 0 0
#> 149 0 0 0 0 0
#> 151 0 1 0 0 0
#> 153 0 0 0 0 0
#> 155 0 1 0 0 0
#> 156 0 0 1 0 0
#> 157 0 0 0 0 0
#> 158 1 0 0 0 0
#> 159 0 1 0 0 0
#> 162 1 0 0 0 0
#> 163 0 1 0 0 0
#> 164 0 0 1 0 0
#> 165 0 0 0 0 0
#> 168 0 0 1 0 0
#> 169 0 0 0 0 0
#> 170 1 0 0 1 0
#> 171 0 1 0 0 1
#> 172 0 0 1 0 0
#> 173 0 0 0 0 0
#> 177 0 0 0 0 0
#> 178 1 0 0 0 0
#> 179 0 1 0 0 0
#> 180 0 0 1 0 0
#> 181 0 0 0 0 0
#> 182 1 0 0 0 0
#> 183 0 1 0 0 0
#> 185 0 0 0 0 0
#> 186 1 0 0 1 0
#> 187 0 1 0 0 1
#> 190 1 0 0 0 0
#> 191 0 1 0 0 0
#> 193 0 0 0 0 0
#> 194 1 0 0 0 0
#> 195 0 1 0 0 0
#> 197 0 0 0 0 0
#> 198 1 0 0 1 0
#> 199 0 1 0 0 1
#> 201 0 0 0 0 0
#> 202 1 0 0 1 0
#> 204 0 0 1 0 0
#> 206 1 0 0 1 0
#> 208 0 0 1 0 0
#> 209 0 0 0 0 0
#> 210 1 0 0 0 0
#> 217 0 0 0 0 0
#> 218 1 0 0 1 0
#> 219 0 1 0 0 1
#> 221 0 0 0 0 0
#> 224 0 0 1 0 0
#> 226 1 0 0 1 0
#> 227 0 1 0 0 1
#> 228 0 0 1 0 0
#> 230 1 0 0 1 0
#> 231 0 1 0 0 1
#> 233 0 0 0 0 0
#> 235 0 1 0 0 1
#> 236 0 0 1 0 0
#> 237 0 0 0 0 0
#> 238 1 0 0 1 0
#> 239 0 1 0 0 1
#> 240 0 0 1 0 0
#> 241 0 0 0 0 0
#> 242 1 0 0 1 0
#> 244 0 0 1 0 0
#> 246 1 0 0 0 0
#> 250 1 0 0 0 0
#> 251 0 1 0 0 0
#> 252 0 0 1 0 0
#> 253 0 0 0 0 0
#> 254 1 0 0 0 0
#> 256 0 0 1 0 0
#> 257 0 0 0 0 0
#> 258 1 0 0 1 0
#> 259 0 1 0 0 1
#> 260 0 0 1 0 0
#> 261 0 0 0 0 0
#> 262 1 0 0 1 0
#> 263 0 1 0 0 1
#> 264 0 0 1 0 0
#> 265 0 0 0 0 0
#> 266 1 0 0 1 0
#> 267 0 1 0 0 1
#> 268 0 0 1 0 0
#> 269 0 0 0 0 0
#> 270 1 0 0 1 0
#> 273 0 0 0 0 0
#> 274 1 0 0 0 0
#> 275 0 1 0 0 0
#> 276 0 0 1 0 0
#> 277 0 0 0 0 0
#> 278 1 0 0 0 0
#> 280 0 0 1 0 0
#> 281 0 0 0 0 0
#> 282 1 0 0 1 0
#> 283 0 1 0 0 1
#> 284 0 0 1 0 0
#> 285 0 0 0 0 0
#> 286 1 0 0 1 0
#> 287 0 1 0 0 1
#> 291 0 1 0 0 0
#> 292 0 0 1 0 0
#> 293 0 0 0 0 0
#> 295 0 1 0 0 0
#> 296 0 0 1 0 0
#> 298 1 0 0 0 0
#> 299 0 1 0 0 0
#> 300 0 0 1 0 0
#> 301 0 0 0 0 0
#> 304 0 0 1 0 0
#> 305 0 0 0 0 0
#> 306 1 0 0 1 0
#> 307 0 1 0 0 1
#> 308 0 0 1 0 0
#> 310 1 0 0 1 0
#> 311 0 1 0 0 1
#> 312 0 0 1 0 0
#> 316 0 0 1 0 0
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#> 318 1 0 0 1 0
#> 319 0 1 0 0 1
#> 322 1 0 0 0 0
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#> 325 0 0 0 0 0
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#> 332 0 0 1 0 0
#> 336 0 0 1 0 0
#> 339 0 1 0 0 0
#> 340 0 0 1 0 0
#> 341 0 0 0 0 0
#> 342 1 0 0 1 0
#> 343 0 1 0 0 1
#> 344 0 0 1 0 0
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#> 351 0 1 0 0 0
#> 352 0 0 1 0 0
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#> 363 0 1 0 0 1
#> 364 0 0 1 0 0
#> 365 0 0 0 0 0
#> 367 0 1 0 0 1
#> 368 0 0 1 0 0
#> 370 1 0 0 0 0
#> 371 0 1 0 0 0
#> 372 0 0 1 0 0
#> 373 0 0 0 0 0
#> 375 0 1 0 0 0
#> 376 0 0 1 0 0
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#> 379 0 1 0 0 0
#> 381 0 0 0 0 0
#> 382 1 0 0 0 0
#> 384 0 0 1 0 0
#> 385 0 0 0 0 0
#> 386 1 0 0 1 0
#> 388 0 0 1 0 0
#> 389 0 0 0 0 0
#> 390 1 0 0 0 0
#> 391 0 1 0 0 0
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#> 398 1 0 0 0 0
#> 399 0 1 0 0 0
#> 402 1 0 0 1 0
#> 403 0 1 0 0 1
#> 405 0 0 0 0 0
#> 406 1 0 0 0 0
#> 407 0 1 0 0 0
#> 408 0 0 1 0 0
#> 409 0 0 0 0 0
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#> 411 0 1 0 0 0
#> 413 0 0 0 0 0
#> 415 0 1 0 0 0
#> 416 0 0 1 0 0
#> 418 1 0 0 1 0
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#> 421 0 0 0 0 0
#> 422 1 0 0 1 0
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#> 444 0 0 1 0 0
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#> 461 0 0 0 0 0
#> 463 0 1 0 0 1
#> 464 0 0 1 0 0
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#> 477 0 0 0 0 0
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#> 496 0 0 1 0 0
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#> 527 0 1 0 0 0
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#> 532 0 0 1 0 0
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#> 535 0 1 0 0 0
#> 536 0 0 1 0 0
#> 537 0 0 0 0 0
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#> 540 0 0 1 0 0
#> 541 0 0 0 0 0
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#> 548 0 0 1 0 0
#> 549 0 0 0 0 0
#> 550 1 0 0 1 0
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#> 557 0 0 0 0 0
#> 558 1 0 0 0 0
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#> 562 1 0 0 1 0
#> 564 0 0 1 0 0
#> 569 0 0 0 0 0
#> 570 1 0 0 1 0
#> 572 0 0 1 0 0
#> 573 0 0 0 0 0
#> 574 1 0 0 0 0
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#> 577 0 0 0 0 0
#> 578 1 0 0 0 0
#> 579 0 1 0 0 0
#> 582 1 0 0 1 0
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#> 584 0 0 1 0 0
#> 585 0 0 0 0 0
#> 586 1 0 0 0 0
#> 587 0 1 0 0 0
#> 590 1 0 0 1 0
#> 591 0 1 0 0 1
#> 593 0 0 0 0 0
#> 594 1 0 0 0 0
#> 595 0 1 0 0 0
#> 596 0 0 1 0 0
#> 599 0 1 0 0 0
#> 600 0 0 1 0 0
#> 601 0 0 0 0 0
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#> 604 0 0 1 0 0
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#> 611 0 1 0 0 0
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#> 616 0 0 1 0 0
#> 617 0 0 0 0 0
#> 619 0 1 0 0 1
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#> 621 0 0 0 0 0
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#> 625 0 0 0 0 0
#> 628 0 0 1 0 0
#> 630 1 0 0 1 0
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#> 634 1 0 0 1 0
#> 638 1 0 0 1 0
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#> 642 1 0 0 0 0
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#> 674 1 0 0 0 0
#> 678 1 0 0 1 0
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#> 680 0 0 1 0 0
#> 682 1 0 0 0 0
#> 684 0 0 1 0 0
#> 685 0 0 0 0 0
#> 686 1 0 0 1 0
#> 687 0 1 0 0 1
#> 689 0 0 0 0 0
#> 690 1 0 0 1 0
#> 691 0 1 0 0 1
#> 693 0 0 0 0 0
#> 694 1 0 0 1 0
#> 695 0 1 0 0 1
#> 697 0 0 0 0 0
#> 698 1 0 0 0 0
#> 700 0 0 1 0 0
#> 701 0 0 0 0 0
#> 702 1 0 0 1 0
#> 704 0 0 1 0 0
#> 707 0 1 0 0 0
#> 709 0 0 0 0 0
#> 712 0 0 1 0 0
#> 713 0 0 0 0 0
#> 715 0 1 0 0 1
#> 716 0 0 1 0 0
#> 717 0 0 0 0 0
#> 718 1 0 0 0 0
#> 719 0 1 0 0 0
#> 721 0 0 0 0 0
#> 723 0 1 0 0 0
#> 724 0 0 1 0 0
#> 727 0 1 0 0 1
#> 728 0 0 1 0 0
#> 729 0 0 0 0 0
#> 730 1 0 0 1 0
#> 734 1 0 0 1 0
#> 736 0 0 1 0 0
#> 738 1 0 0 0 0
#> 739 0 1 0 0 0
#> 740 0 0 1 0 0
#> 741 0 0 0 0 0
#> 742 1 0 0 0 0
#> 744 0 0 1 0 0
#> 745 0 0 0 0 0
#> 749 0 0 0 0 0
#> 751 0 1 0 0 0
#> 753 0 0 0 0 0
#> 754 1 0 0 1 0
#> 755 0 1 0 0 1
#> 757 0 0 0 0 0
#> 758 1 0 0 1 0
#> 759 0 1 0 0 1
#> 760 0 0 1 0 0
#> 761 0 0 0 0 0
#> 764 0 0 1 0 0
#> 765 0 0 0 0 0
#> 766 1 0 0 1 0
#> 767 0 1 0 0 1
#> 768 0 0 1 0 0
#> 770 1 0 0 0 0
#> 771 0 1 0 0 0
#> 772 0 0 1 0 0
#> 773 0 0 0 0 0
#> 774 1 0 0 0 0
#> 775 0 1 0 0 0
#> 776 0 0 1 0 0
#> 778 1 0 0 1 0
#> 779 0 1 0 0 1
#> 781 0 0 0 0 0
#> 782 1 0 0 0 0
#> 784 0 0 1 0 0
#> 788 0 0 1 0 0
#> 789 0 0 0 0 0
#> 790 1 0 0 1 0
#> 792 0 0 1 0 0
#> 797 0 0 0 0 0
#> 798 1 0 0 0 0
#> 800 0 0 1 0 0
#> ARMCDTRT:AVISITVIS4
#> 2 0
#> 4 1
#> 6 0
#> 7 0
#> 8 0
#> 10 0
#> 12 0
#> 13 0
#> 14 0
#> 16 1
#> 17 0
#> 19 0
#> 20 0
#> 23 0
#> 25 0
#> 26 0
#> 28 0
#> 29 0
#> 30 0
#> 31 0
#> 32 0
#> 33 0
#> 34 0
#> 36 1
#> 39 0
#> 41 0
#> 42 0
#> 43 0
#> 44 1
#> 45 0
#> 46 0
#> 47 0
#> 51 0
#> 52 1
#> 55 0
#> 59 0
#> 60 0
#> 62 0
#> 64 0
#> 65 0
#> 68 0
#> 69 0
#> 70 0
#> 72 1
#> 73 0
#> 74 0
#> 75 0
#> 76 1
#> 78 0
#> 79 0
#> 82 0
#> 83 0
#> 84 1
#> 85 0
#> 86 0
#> 87 0
#> 88 1
#> 89 0
#> 90 0
#> 91 0
#> 93 0
#> 94 0
#> 95 0
#> 96 1
#> 97 0
#> 98 0
#> 99 0
#> 100 1
#> 101 0
#> 102 0
#> 103 0
#> 104 1
#> 105 0
#> 107 0
#> 108 1
#> 109 0
#> 110 0
#> 111 0
#> 112 1
#> 113 0
#> 114 0
#> 116 1
#> 117 0
#> 118 0
#> 119 0
#> 120 1
#> 121 0
#> 123 0
#> 125 0
#> 128 1
#> 129 0
#> 130 0
#> 132 1
#> 133 0
#> 134 0
#> 135 0
#> 136 0
#> 137 0
#> 138 0
#> 140 1
#> 142 0
#> 144 1
#> 145 0
#> 146 0
#> 147 0
#> 148 0
#> 149 0
#> 151 0
#> 153 0
#> 155 0
#> 156 0
#> 157 0
#> 158 0
#> 159 0
#> 162 0
#> 163 0
#> 164 0
#> 165 0
#> 168 0
#> 169 0
#> 170 0
#> 171 0
#> 172 1
#> 173 0
#> 177 0
#> 178 0
#> 179 0
#> 180 0
#> 181 0
#> 182 0
#> 183 0
#> 185 0
#> 186 0
#> 187 0
#> 190 0
#> 191 0
#> 193 0
#> 194 0
#> 195 0
#> 197 0
#> 198 0
#> 199 0
#> 201 0
#> 202 0
#> 204 1
#> 206 0
#> 208 1
#> 209 0
#> 210 0
#> 217 0
#> 218 0
#> 219 0
#> 221 0
#> 224 0
#> 226 0
#> 227 0
#> 228 1
#> 230 0
#> 231 0
#> 233 0
#> 235 0
#> 236 1
#> 237 0
#> 238 0
#> 239 0
#> 240 1
#> 241 0
#> 242 0
#> 244 1
#> 246 0
#> 250 0
#> 251 0
#> 252 0
#> 253 0
#> 254 0
#> 256 0
#> 257 0
#> 258 0
#> 259 0
#> 260 1
#> 261 0
#> 262 0
#> 263 0
#> 264 1
#> 265 0
#> 266 0
#> 267 0
#> 268 1
#> 269 0
#> 270 0
#> 273 0
#> 274 0
#> 275 0
#> 276 0
#> 277 0
#> 278 0
#> 280 0
#> 281 0
#> 282 0
#> 283 0
#> 284 1
#> 285 0
#> 286 0
#> 287 0
#> 291 0
#> 292 0
#> 293 0
#> 295 0
#> 296 0
#> 298 0
#> 299 0
#> 300 0
#> 301 0
#> 304 1
#> 305 0
#> 306 0
#> 307 0
#> 308 1
#> 310 0
#> 311 0
#> 312 1
#> 316 0
#> 317 0
#> 318 0
#> 319 0
#> 322 0
#> 323 0
#> 324 0
#> 325 0
#> 327 0
#> 328 0
#> 329 0
#> 330 0
#> 331 0
#> 332 1
#> 336 0
#> 339 0
#> 340 0
#> 341 0
#> 342 0
#> 343 0
#> 344 1
#> 345 0
#> 347 0
#> 349 0
#> 351 0
#> 352 0
#> 353 0
#> 354 0
#> 355 0
#> 356 0
#> 357 0
#> 363 0
#> 364 1
#> 365 0
#> 367 0
#> 368 1
#> 370 0
#> 371 0
#> 372 0
#> 373 0
#> 375 0
#> 376 0
#> 378 0
#> 379 0
#> 381 0
#> 382 0
#> 384 0
#> 385 0
#> 386 0
#> 388 1
#> 389 0
#> 390 0
#> 391 0
#> 392 0
#> 394 0
#> 397 0
#> 398 0
#> 399 0
#> 402 0
#> 403 0
#> 405 0
#> 406 0
#> 407 0
#> 408 0
#> 409 0
#> 410 0
#> 411 0
#> 413 0
#> 415 0
#> 416 0
#> 418 0
#> 419 0
#> 421 0
#> 422 0
#> 423 0
#> 424 1
#> 427 0
#> 428 0
#> 429 0
#> 430 0
#> 431 0
#> 432 1
#> 434 0
#> 435 0
#> 436 0
#> 438 0
#> 439 0
#> 444 0
#> 445 0
#> 447 0
#> 449 0
#> 450 0
#> 451 0
#> 453 0
#> 454 0
#> 455 0
#> 456 0
#> 457 0
#> 458 0
#> 459 0
#> 461 0
#> 463 0
#> 464 1
#> 465 0
#> 469 0
#> 470 0
#> 471 0
#> 473 0
#> 474 0
#> 477 0
#> 484 1
#> 487 0
#> 489 0
#> 490 0
#> 491 0
#> 494 0
#> 495 0
#> 496 1
#> 497 0
#> 498 0
#> 499 0
#> 501 0
#> 502 0
#> 504 1
#> 505 0
#> 508 1
#> 509 0
#> 510 0
#> 511 0
#> 512 1
#> 513 0
#> 518 0
#> 519 0
#> 521 0
#> 522 0
#> 523 0
#> 524 0
#> 526 0
#> 527 0
#> 528 0
#> 530 0
#> 531 0
#> 532 0
#> 534 0
#> 535 0
#> 536 0
#> 537 0
#> 538 0
#> 539 0
#> 540 0
#> 541 0
#> 544 1
#> 545 0
#> 546 0
#> 547 0
#> 548 1
#> 549 0
#> 550 0
#> 551 0
#> 555 0
#> 556 1
#> 557 0
#> 558 0
#> 560 0
#> 562 0
#> 564 1
#> 569 0
#> 570 0
#> 572 1
#> 573 0
#> 574 0
#> 575 0
#> 576 0
#> 577 0
#> 578 0
#> 579 0
#> 582 0
#> 583 0
#> 584 1
#> 585 0
#> 586 0
#> 587 0
#> 590 0
#> 591 0
#> 593 0
#> 594 0
#> 595 0
#> 596 0
#> 599 0
#> 600 0
#> 601 0
#> 602 0
#> 604 0
#> 606 0
#> 608 1
#> 609 0
#> 610 0
#> 611 0
#> 612 0
#> 613 0
#> 614 0
#> 616 0
#> 617 0
#> 619 0
#> 620 1
#> 621 0
#> 622 0
#> 623 0
#> 624 0
#> 625 0
#> 628 1
#> 630 0
#> 631 0
#> 632 1
#> 633 0
#> 634 0
#> 638 0
#> 639 0
#> 640 1
#> 642 0
#> 645 0
#> 648 0
#> 650 0
#> 652 0
#> 654 0
#> 655 0
#> 656 0
#> 657 0
#> 661 0
#> 665 0
#> 666 0
#> 668 0
#> 669 0
#> 670 0
#> 671 0
#> 673 0
#> 674 0
#> 678 0
#> 679 0
#> 680 1
#> 682 0
#> 684 0
#> 685 0
#> 686 0
#> 687 0
#> 689 0
#> 690 0
#> 691 0
#> 693 0
#> 694 0
#> 695 0
#> 697 0
#> 698 0
#> 700 0
#> 701 0
#> 702 0
#> 704 1
#> 707 0
#> 709 0
#> 712 0
#> 713 0
#> 715 0
#> 716 1
#> 717 0
#> 718 0
#> 719 0
#> 721 0
#> 723 0
#> 724 0
#> 727 0
#> 728 1
#> 729 0
#> 730 0
#> 734 0
#> 736 1
#> 738 0
#> 739 0
#> 740 0
#> 741 0
#> 742 0
#> 744 0
#> 745 0
#> 749 0
#> 751 0
#> 753 0
#> 754 0
#> 755 0
#> 757 0
#> 758 0
#> 759 0
#> 760 1
#> 761 0
#> 764 1
#> 765 0
#> 766 0
#> 767 0
#> 768 1
#> 770 0
#> 771 0
#> 772 0
#> 773 0
#> 774 0
#> 775 0
#> 776 0
#> 778 0
#> 779 0
#> 781 0
#> 782 0
#> 784 0
#> 788 0
#> 789 0
#> 790 0
#> 792 1
#> 797 0
#> 798 0
#> 800 0
#> attr(,"assign")
#> [1] 0 1 1 2 3 4 4 4 5 5 5
#> attr(,"contrasts")
#> attr(,"contrasts")$RACE
#> Black or African American White
#> Asian 0 0
#> Black or African American 1 0
#> White 0 1
#>
#> attr(,"contrasts")$SEX
#> Female
#> Male 0
#> Female 1
#>
#> attr(,"contrasts")$ARMCD
#> TRT
#> PBO 0
#> TRT 1
#>
#> attr(,"contrasts")$AVISIT
#> VIS2 VIS3 VIS4
#> VIS1 0 0 0
#> VIS2 1 0 0
#> VIS3 0 1 0
#> VIS4 0 0 1
#>
#>
#> $y_vector
#> [1] 39.97105 20.48379 31.45522 36.87889 48.80809 35.98699 37.16444 33.89229
#> [9] 33.74637 54.45055 32.31386 46.79361 41.71154 39.02423 31.93050 32.90947
#> [17] 48.28031 32.23021 35.91080 45.54898 53.02877 47.16898 46.64287 58.09713
#> [25] 44.97613 44.32755 38.97813 43.72862 46.43393 40.34576 42.76568 40.11155
#> [33] 53.31791 56.07641 41.90837 34.65663 39.07791 35.89612 47.67264 22.65440
#> [41] 40.85376 32.60048 33.64329 40.92278 32.14831 46.43604 41.34973 66.30382
#> [49] 47.95358 53.97364 56.64544 49.70872 60.40497 45.98525 51.90911 41.50787
#> [57] 53.42727 23.86859 35.98563 43.60626 29.59773 35.50688 55.42944 52.10530
#> [65] 31.69644 32.16159 51.04735 55.85987 49.11706 49.25544 51.72211 69.99128
#> [73] 22.07169 46.08393 52.42288 37.69466 44.59400 52.08897 58.22961 37.22824
#> [81] 34.39863 36.34012 45.44182 41.54847 43.92172 61.83243 27.25656 45.65133
#> [89] 33.19334 41.66826 27.12753 31.74858 41.60000 39.45250 32.61823 34.62445
#> [97] 45.90515 36.17780 39.79796 50.08272 44.64316 39.73529 34.06164 40.18592
#> [105] 41.17584 57.76669 38.18460 47.19893 37.32785 43.16048 41.40349 30.15733
#> [113] 35.84353 40.95250 41.37928 50.17316 45.35226 39.06491 42.11960 29.81042
#> [121] 42.57055 47.81652 68.06024 35.62071 33.89134 36.42808 37.57519 58.46873
#> [129] 19.54516 31.13541 40.89955 22.18809 41.05857 37.32452 43.12432 41.99349
#> [137] 44.03080 38.66417 53.45993 29.81948 30.43859 40.18095 26.78578 34.55115
#> [145] 40.06421 43.09329 45.71567 40.74992 44.74635 40.14674 48.75859 46.43462
#> [153] 29.33990 47.93165 41.11632 47.05889 52.24599 54.14236 50.44618 37.53657
#> [161] 49.45840 59.12866 40.31268 39.66049 50.89726 56.13116 32.82981 46.53837
#> [169] 51.81265 29.91939 51.05656 50.50059 64.11388 32.21843 29.64732 45.09919
#> [177] 39.75659 37.28894 44.80145 65.95920 33.43439 33.57042 39.91543 49.57098
#> [185] 38.91634 36.69011 45.66665 52.07431 42.21411 45.02901 30.98338 44.72932
#> [193] 40.68711 34.71530 27.30752 37.31585 44.83000 32.93042 44.91911 45.68636
#> [201] 65.98800 46.60130 40.89786 46.66708 43.83270 44.11604 38.29612 51.38570
#> [209] 56.20979 43.45819 38.38741 56.42818 39.05050 54.09200 31.40521 46.13330
#> [217] 45.29845 28.06936 42.50283 46.45368 64.97366 43.97847 35.33466 39.34378
#> [225] 41.27633 39.83058 43.49673 44.06114 41.43742 46.16954 54.24024 36.61831
#> [233] 42.09272 50.69556 51.72563 53.89947 39.94420 56.42482 41.86385 34.56420
#> [241] 38.68927 62.88743 28.85343 49.29495 28.74029 43.59994 57.38616 35.36824
#> [249] 43.06110 31.27551 54.13245 25.97050 51.17493 48.44043 43.33128 55.93546
#> [257] 54.15312 40.60252 44.44715 40.54161 33.95563 43.67802 42.76023 42.82678
#> [265] 39.59218 33.49216 35.39266 42.36266 48.54368 43.94366 47.91204 20.72928
#> [273] 28.00599 40.19255 37.79360 36.75177 34.59822 39.32034 40.65702 43.03255
#> [281] 54.65715 35.55742 43.70215 42.52157 54.89337 32.03460 29.45107 45.35138
#> [289] 38.73784 41.42283 47.32385 47.55310 49.06509 29.22591 40.08175 45.68142
#> [297] 41.47403 42.51970 69.36099 42.39760 43.72376 49.47601 51.94188 40.59100
#> [305] 39.97833 31.69049 37.20517 46.28740 41.58720 32.17365 40.69375 32.28771
#> [313] 41.76205 40.06768 29.14213 39.50989 43.32349 47.16756 40.93020 42.19406
#> [321] 41.21057 38.54330 43.96324 42.67652 22.79584 31.43559 38.85064 48.24288
#> [329] 44.71302 51.85370 30.56757 59.90473 49.76150 47.21985 40.34525 48.29793
#> [337] 44.39634 41.71421 47.37535 42.03797 37.56100 45.11793 34.62530 45.28206
#> [345] 63.57761 35.80878 52.67314 35.88734 38.73222 46.70361 53.65398 36.71543
#> [353] 41.54317 51.67909 27.40130 30.33517 37.73092 29.11668 32.08830 41.66067
#> [361] 53.90815 35.06937 47.17615 56.49347 38.88006 47.54070 43.53705 31.82054
#> [369] 39.62816 44.95543 21.11543 34.74671 56.69249 22.73126 32.50075 42.37206
#> [377] 42.89847 55.62582 45.38998 52.66743 34.18931 45.59740 28.89198 38.46147
#> [385] 49.90357 44.14167 55.24278 27.38001 33.63251 39.34410 26.98575 24.04175
#> [393] 42.16648 44.75380 31.55469 44.42696 44.10343 37.87445 48.31828 50.21520
#> [401] 41.94615 39.62690 46.69763 43.75255 47.38873 32.43412 43.07163 42.99551
#> [409] 53.82759 50.64802 63.44051 34.48949 40.08056 47.46553 37.11697 36.25120
#> [417] 29.20171 31.53773 42.35683 64.78352 32.72757 37.50022 57.03861 36.32475
#> [425] 41.46725 59.01411 30.14970 34.91740 52.13900 58.73839 35.83185 56.41409
#> [433] 43.55593 44.26320 59.25579 28.47314 47.47581 46.47483 51.22677 45.82777
#> [441] 39.06783 29.99542 54.17796 44.55743 62.59579 35.48396 44.07768 46.57837
#> [449] 47.67979 22.15439 34.27765 36.90059 40.54285 29.09494 37.21768 43.08491
#> [457] 27.12174 34.11916 40.80230 45.89269 43.69153 29.22869 55.68362 31.90698
#> [465] 37.31061 40.75546 42.19474 44.87228 47.55198 50.62894 45.47551 48.62168
#> [473] 29.66493 34.57406 38.11676 33.77204 34.26148 58.81037 39.88119 31.62708
#> [481] 48.22049 42.58829 49.33262 53.74331 29.71857 30.45651 38.29800 36.81040
#> [489] 42.35045 39.39860 49.73629 41.58082 43.58901 40.16762 41.08206 69.37409
#> [497] 41.27625 44.76138 39.69815 38.44296 48.20586 35.50735 32.08153 44.69256
#> [505] 42.18689 37.01741 38.26920 49.28806 40.45953 45.10337 45.58250 62.96989
#> [513] 30.78252 44.69667 32.72491 45.78702 48.74886 84.08449 30.19495 36.78573
#> [521] 61.03588 20.36749 35.22480 37.42847 30.20501 49.12862 47.31234 19.28388
#> [529] 30.00682 49.21768 40.13353 42.34534 52.32575 69.26254 35.70341 41.64454
#> [537] 54.25081
#>
#> $neg_log_lik
#> [1] 1693.225
#>
#> $jac_list
#> $jac_list[[1]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.16951547 -0.051411669 -0.0450053577 -0.029651633 -1.11563537
#> [2,] -0.05141167 0.087578417 0.0345764451 0.007196977 0.00260112
#> [3,] -0.04500536 0.034576445 0.0850344790 0.007128258 -0.01178718
#> [4,] -0.02965163 0.007196977 0.0071282583 0.061521074 -0.01065994
#> [5,] -1.11563537 0.002601120 -0.0117871834 -0.010659937 2.28786967
#> [6,] -0.98171081 0.004118345 0.0089518223 -0.003655354 0.97932241
#> [7,] -1.07753684 0.005790797 0.0100023530 -0.006895078 1.07595394
#> [8,] -0.99821296 -0.001933165 0.0086761892 -0.005754318 0.99903467
#> [9,] 0.97217159 0.008520375 0.0132545932 0.002102199 -1.98758938
#> [10,] 1.06909044 0.008539116 0.0053378784 0.004325848 -2.18658687
#> [11,] 0.99545698 0.001249297 0.0000785895 0.008328731 -2.01758658
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -0.981710811 -1.077536844 -0.998212960 0.972171586 1.069090436
#> [2,] 0.004118345 0.005790797 -0.001933165 0.008520375 0.008539116
#> [3,] 0.008951822 0.010002353 0.008676189 0.013254593 0.005337878
#> [4,] -0.003655354 -0.006895078 -0.005754318 0.002102199 0.004325848
#> [5,] 0.979322409 1.075953942 0.999034668 -1.987589379 -2.186586867
#> [6,] 0.836813950 0.933379638 0.857077689 -0.836557168 -0.933038454
#> [7,] 0.933379638 1.029968833 0.953510481 -0.932874939 -1.029216841
#> [8,] 0.857077689 0.953510481 0.877307817 -0.857056128 -0.953603898
#> [9,] -0.836557168 -0.932874939 -0.857056128 1.689099664 1.888995410
#> [10,] -0.933038454 -1.029216841 -0.953603898 1.888995410 2.089042080
#> [11,] -0.857161705 -0.953646838 -0.877357597 1.718938218 1.919022103
#> [,11]
#> [1,] 0.9954569814
#> [2,] 0.0012492968
#> [3,] 0.0000785895
#> [4,] 0.0083287309
#> [5,] -2.0175865751
#> [6,] -0.8571617054
#> [7,] -0.9536468379
#> [8,] -0.8773575973
#> [9,] 1.7189382180
#> [10,] 1.9190221026
#> [11,] 1.7497813115
#>
#> $jac_list[[2]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.1275306312 -0.129971302 -0.0910717692 -0.098349416 -0.0096292730
#> [2,] -0.1299713021 0.223312665 0.1008449781 0.022808956 0.0192625868
#> [3,] -0.0910717692 0.100844978 0.2411274630 0.008554981 -0.0182023655
#> [4,] -0.0983494163 0.022808956 0.0085549805 0.158588894 0.0074601050
#> [5,] -0.0096292730 0.019262587 -0.0182023655 0.007460105 0.0052924415
#> [6,] 0.1435399949 -0.001146971 -0.0062318230 0.002417212 -0.1423316326
#> [7,] -0.0054058828 0.005303578 -0.0057570500 0.007567400 0.0017862783
#> [8,] -0.0009468737 -0.001369925 -0.0089479596 0.005898220 0.0012090248
#> [9,] -0.1357904146 -0.003851407 -0.0054496317 -0.008289146 0.2986740317
#> [10,] 0.0090279320 0.004055441 -0.0009261889 -0.019591078 0.0003322176
#> [11,] 0.0105498524 -0.009420670 -0.0019295670 -0.011019805 -0.0012298550
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] 0.143539995 -0.0054058828 -0.0009468737 -0.135790415 0.0090279320
#> [2,] -0.001146971 0.0053035777 -0.0013699252 -0.003851407 0.0040554409
#> [3,] -0.006231823 -0.0057570500 -0.0089479596 -0.005449632 -0.0009261889
#> [4,] 0.002417212 0.0075673997 0.0058982201 -0.008289146 -0.0195910778
#> [5,] -0.142331633 0.0017862783 0.0012090248 0.298674032 0.0003322176
#> [6,] 0.448003739 -0.1162181844 -0.0706352008 -0.448120908 0.1161018057
#> [7,] -0.116218184 0.0006208091 0.0004239333 0.115940070 -0.0006363702
#> [8,] -0.070635201 0.0004239333 0.0004185595 0.070507365 -0.0006302980
#> [9,] -0.448120908 0.1159400700 0.0705073652 0.858765561 -0.2400454621
#> [10,] 0.116101806 -0.0006363702 -0.0006302980 -0.240045462 0.0023653114
#> [11,] 0.070632348 -0.0007028853 -0.0003653047 -0.146687106 0.0008087297
#> [,11]
#> [1,] 0.0105498524
#> [2,] -0.0094206701
#> [3,] -0.0019295670
#> [4,] -0.0110198053
#> [5,] -0.0012298550
#> [6,] 0.0706323476
#> [7,] -0.0007028853
#> [8,] -0.0003653047
#> [9,] -0.1466871056
#> [10,] 0.0008087297
#> [11,] 0.0008254937
#>
#> $jac_list[[3]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.245560091 -0.241005288 -0.199099088 -0.186929231 -0.007083200
#> [2,] -0.241005288 0.415633400 0.207029802 0.031893969 0.028836257
#> [3,] -0.199099088 0.207029802 0.500748613 0.030611285 -0.048411146
#> [4,] -0.186929231 0.031893969 0.030611285 0.306670056 0.005230923
#> [5,] -0.007083200 0.028836257 -0.048411146 0.005230923 0.011939767
#> [6,] -0.006054804 0.001585372 -0.007248864 0.012399309 0.001516357
#> [7,] 0.038517950 0.007606844 -0.008011985 0.011376159 -0.044066774
#> [8,] -0.002604366 0.001058044 -0.013637332 0.008572980 0.002399258
#> [9,] 0.007160701 0.005781258 0.015632421 -0.023181005 -0.001960056
#> [10,] -0.036322393 0.009928402 0.006711191 -0.029277060 0.097958291
#> [11,] 0.012868838 -0.013894309 0.004513448 -0.013783909 -0.002935595
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -0.0060548037 0.038517950 -0.0026043657 0.007160701 -0.036322393
#> [2,] 0.0015853720 0.007606844 0.0010580439 0.005781258 0.009928402
#> [3,] -0.0072488639 -0.008011985 -0.0136373324 0.015632421 0.006711191
#> [4,] 0.0123993094 0.011376159 0.0085729799 -0.023181005 -0.029277060
#> [5,] 0.0015163570 -0.044066774 0.0023992582 -0.001960056 0.097958291
#> [6,] 0.0005531212 -0.019244874 0.0005443284 -0.001131917 0.018650673
#> [7,] -0.0192448740 0.322767842 -0.0369215897 0.018771762 -0.322953100
#> [8,] 0.0005443284 -0.036921590 0.0006655006 -0.001070581 0.036691455
#> [9,] -0.0011319169 0.018771762 -0.0010705809 0.002312297 -0.037787975
#> [10,] 0.0186506731 -0.322953100 0.0366914553 -0.037787975 0.729050666
#> [11,] -0.0007378620 0.036578230 -0.0007538174 0.001139903 -0.078301890
#> [,11]
#> [1,] 0.0128688383
#> [2,] -0.0138943092
#> [3,] 0.0045134481
#> [4,] -0.0137839090
#> [5,] -0.0029355953
#> [6,] -0.0007378620
#> [7,] 0.0365782297
#> [8,] -0.0007538174
#> [9,] 0.0011399033
#> [10,] -0.0783018897
#> [11,] 0.0012934309
#>
#> $jac_list[[4]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.029388061 -0.0300363972 -0.0190464016 -0.0219001535 -0.0026139703
#> [2,] -0.030036397 0.0534144734 0.0204813833 0.0011759493 0.0060482952
#> [3,] -0.019046402 0.0204813833 0.0591610472 0.0004350294 -0.0075372942
#> [4,] -0.021900153 0.0011759493 0.0004350294 0.0391623541 0.0015980966
#> [5,] -0.002613970 0.0060482952 -0.0075372942 0.0015980966 0.0024815727
#> [6,] -0.001287289 0.0013882825 -0.0017696952 0.0017825394 0.0005500661
#> [7,] -0.001819822 0.0029497206 -0.0021392898 0.0014943282 0.0008816109
#> [8,] 0.120475742 0.0066564090 -0.0025523369 -0.0005390796 -0.1213358437
#> [9,] 0.001514454 0.0003149104 0.0035339826 -0.0042346457 -0.0006413058
#> [10,] 0.001998149 0.0003181908 0.0023183532 -0.0048503189 -0.0004152991
#> [11,] -0.121026181 -0.0031128838 0.0032728586 -0.0016022973 0.2665382626
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -0.0012872891 -0.0018198219 0.1204757422 0.0015144537 0.0019981493
#> [2,] 0.0013882825 0.0029497206 0.0066564090 0.0003149104 0.0003181908
#> [3,] -0.0017696952 -0.0021392898 -0.0025523369 0.0035339826 0.0023183532
#> [4,] 0.0017825394 0.0014943282 -0.0005390796 -0.0042346457 -0.0048503189
#> [5,] 0.0005500661 0.0008816109 -0.1213358437 -0.0006413058 -0.0004152991
#> [6,] 0.0001286007 0.0001813006 -0.0503065912 -0.0002302344 -0.0001918273
#> [7,] 0.0001813006 0.0002904376 -0.1134126363 -0.0002434026 -0.0001634397
#> [8,] -0.0503065912 -0.1134126363 2.5685656977 0.0503712957 0.1139567512
#> [9,] -0.0002302344 -0.0002434026 0.0503712957 0.0005410877 0.0005376701
#> [10,] -0.0001918273 -0.0001634397 0.1139567512 0.0005376701 0.0005457575
#> [11,] 0.0502540493 0.1134358458 -2.5686970395 -0.1159679830 -0.2486909707
#> [,11]
#> [1,] -0.121026181
#> [2,] -0.003112884
#> [3,] 0.003272859
#> [4,] -0.001602297
#> [5,] 0.266538263
#> [6,] 0.050254049
#> [7,] 0.113435846
#> [8,] -2.568697039
#> [9,] -0.115967983
#> [10,] -0.248690971
#> [11,] 5.099408635
#>
#> $jac_list[[5]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.004551316 -0.0879251088 -0.0675549695 -0.0619695010 0.082243669
#> [2,] -0.087925109 0.1485375633 0.0683640555 0.0155723082 0.009620691
#> [3,] -0.067554970 0.0683640555 0.1594567206 0.0077525334 -0.017394272
#> [4,] -0.061969501 0.0155723082 0.0077525334 0.1048824324 -0.005511091
#> [5,] 0.082243669 0.0096206906 -0.0173942723 -0.0055110912 -0.156537882
#> [6,] 0.385905592 -0.0011341107 0.0027606977 -0.0059892149 -0.383415856
#> [7,] 0.077428636 0.0046614852 0.0022487030 0.0005457593 -0.079946648
#> [8,] 0.084542958 -0.0004665567 0.0005575601 -0.0003711182 -0.084356478
#> [9,] -0.386649427 -0.0035180887 -0.0074083951 0.0127403370 0.789358432
#> [10,] -0.082343916 0.0054837328 0.0048099473 -0.0025669755 0.163052708
#> [11,] -0.085004957 -0.0033454411 0.0014294625 0.0037285530 0.162124303
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] 0.385905592 0.0774286360 0.0845429582 -0.386649427 -0.082343916
#> [2,] -0.001134111 0.0046614852 -0.0004665567 -0.003518089 0.005483733
#> [3,] 0.002760698 0.0022487030 0.0005575601 -0.007408395 0.004809947
#> [4,] -0.005989215 0.0005457593 -0.0003711182 0.012740337 -0.002566976
#> [5,] -0.383415856 -0.0799466479 -0.0843564778 0.789358432 0.163052708
#> [6,] -0.453414690 -0.3488427143 -0.2936422302 0.453945774 0.349184039
#> [7,] -0.348842714 -0.0807840816 -0.0848246967 0.349077736 0.081076804
#> [8,] -0.293642230 -0.0848246967 -0.0924408763 0.293908832 0.084761720
#> [9,] 0.453945774 0.3490777358 0.2939088316 -0.944430402 -0.718327934
#> [10,] 0.349184039 0.0810768042 0.0847617197 -0.718327934 -0.165357544
#> [11,] 0.293825856 0.0847300389 0.0924354630 -0.593948987 -0.164508835
#> [,11]
#> [1,] -0.085004957
#> [2,] -0.003345441
#> [3,] 0.001429462
#> [4,] 0.003728553
#> [5,] 0.162124303
#> [6,] 0.293825856
#> [7,] 0.084730039
#> [8,] 0.092435463
#> [9,] -0.593948987
#> [10,] -0.164508835
#> [11,] -0.172559426
#>
#> $jac_list[[6]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.08542158 -0.137826562 -0.128270224 -0.078379266 0.05003098
#> [2,] -0.13782656 0.220960935 0.114251875 0.018491525 0.01153614
#> [3,] -0.12827022 0.114251875 0.261843779 0.019186952 -0.02405239
#> [4,] -0.07837927 0.018491525 0.019186952 0.160356325 -0.01893061
#> [5,] 0.05003098 0.011536140 -0.024052393 -0.018930605 -0.06335921
#> [6,] 0.03659983 0.008950647 0.015700461 -0.014175944 -0.03717414
#> [7,] 0.26882833 0.006132241 0.015058304 -0.015518470 -0.26769477
#> [8,] 0.04288401 0.005444285 0.015721157 -0.017201177 -0.04062223
#> [9,] -0.04557652 0.006113619 0.007583599 0.007848601 0.06486010
#> [10,] -0.27641022 0.002373388 0.000309449 0.014331909 0.54658686
#> [11,] -0.04574165 -0.002160890 -0.003210129 0.015234860 0.06878771
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] 0.036599825 0.268828329 0.042884008 -0.045576525 -0.276410217
#> [2,] 0.008950647 0.006132241 0.005444285 0.006113619 0.002373388
#> [3,] 0.015700461 0.015058304 0.015721157 0.007583599 0.000309449
#> [4,] -0.014175944 -0.015518470 -0.017201177 0.007848601 0.014331909
#> [5,] -0.037174140 -0.267694771 -0.040622229 0.064860104 0.546586858
#> [6,] -0.036537526 -0.182235351 -0.036883214 0.037420938 0.183580391
#> [7,] -0.182235351 -0.430330046 -0.191856061 0.183200040 0.431352140
#> [8,] -0.036883214 -0.191856061 -0.040133148 0.037660138 0.192906564
#> [9,] 0.037420938 0.183200040 0.037660138 -0.066023554 -0.369293971
#> [10,] 0.183580391 0.431352140 0.192906564 -0.369293971 -0.890527917
#> [11,] 0.036772746 0.191909626 0.039985136 -0.065412138 -0.388112965
#> [,11]
#> [1,] -0.045741650
#> [2,] -0.002160890
#> [3,] -0.003210129
#> [4,] 0.015234860
#> [5,] 0.068787709
#> [6,] 0.036772746
#> [7,] 0.191909626
#> [8,] 0.039985136
#> [9,] -0.065412138
#> [10,] -0.388112965
#> [11,] -0.069601482
#>
#> $jac_list[[7]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.114086175 -0.097427416 -0.083769145 -0.084335895 -0.015177898
#> [2,] -0.097427416 0.171565410 0.091327221 0.014994572 0.012589378
#> [3,] -0.083769145 0.091327221 0.214271278 0.021099078 -0.018328293
#> [4,] -0.084335895 0.014994572 0.021099078 0.128252725 0.003057877
#> [5,] -0.015177898 0.012589378 -0.018328293 0.003057877 0.026047603
#> [6,] -0.004551890 -0.009562539 -0.014683447 -0.005348838 0.015231555
#> [7,] -0.007876719 -0.005961612 -0.011655743 0.002717432 0.012237857
#> [8,] -0.010527501 -0.005408481 -0.012494864 0.007646904 0.012257413
#> [9,] 0.015278321 -0.001787168 -0.003423079 0.002034905 -0.026811775
#> [10,] 0.016026962 -0.001839695 0.001582605 -0.006787331 -0.021212859
#> [11,] 0.017090675 -0.004524007 0.001369912 -0.007745888 -0.022343973
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -0.004551890 -0.007876719 -0.010527501 0.015278321 0.016026962
#> [2,] -0.009562539 -0.005961612 -0.005408481 -0.001787168 -0.001839695
#> [3,] -0.014683447 -0.011655743 -0.012494864 -0.003423079 0.001582605
#> [4,] -0.005348838 0.002717432 0.007646904 0.002034905 -0.006787331
#> [5,] 0.015231555 0.012237857 0.012257413 -0.026811775 -0.021212859
#> [6,] 0.004657887 0.186432601 0.014340668 -0.004729216 -0.186448882
#> [7,] 0.186432601 0.028282920 0.031912916 -0.186868015 -0.028980205
#> [8,] 0.014340668 0.031912916 0.011976149 -0.014607480 -0.032546102
#> [9,] -0.004729216 -0.186868015 -0.014607480 0.011985702 0.401133296
#> [10,] -0.186448882 -0.028980205 -0.032546102 0.401133296 0.054465603
#> [11,] -0.013914903 -0.031751354 -0.011780294 0.026473177 0.067484739
#> [,11]
#> [1,] 0.017090675
#> [2,] -0.004524007
#> [3,] 0.001369912
#> [4,] -0.007745888
#> [5,] -0.022343973
#> [6,] -0.013914903
#> [7,] -0.031751354
#> [8,] -0.011780294
#> [9,] 0.026473177
#> [10,] 0.067484739
#> [11,] 0.021879293
#>
#> $jac_list[[8]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] -0.006323446 -0.0330247366 -0.0306335901 -2.713874e-02 0.0429007221
#> [2,] -0.033024737 0.0689271629 0.0264214269 3.098127e-03 0.0007687077
#> [3,] -0.030633590 0.0264214269 0.0727011520 2.052435e-03 -0.0042893481
#> [4,] -0.027138741 0.0030981272 0.0020524350 5.004350e-02 -0.0033130635
#> [5,] 0.042900722 0.0007687077 -0.0042893481 -3.313064e-03 -0.0739170777
#> [6,] 0.037776600 -0.0029030175 0.0031236253 -8.298186e-05 -0.0379760317
#> [7,] 0.040175431 -0.0026049030 0.0036099238 -3.983308e-04 -0.0404707348
#> [8,] 0.596038716 0.0125429026 0.0064458746 -7.951491e-03 -0.5979172824
#> [9,] -0.039473964 0.0048333133 -0.0003088884 5.586363e-04 0.0703908752
#> [10,] -0.041733451 0.0069117337 -0.0021797920 -2.391215e-04 0.0750270535
#> [11,] -0.606706604 0.0066710180 0.0026709546 8.298983e-03 1.2937347672
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] 3.777660e-02 0.0401754313 0.596038716 -0.0394739639 -0.0417334514
#> [2,] -2.903018e-03 -0.0026049030 0.012542903 0.0048333133 0.0069117337
#> [3,] 3.123625e-03 0.0036099238 0.006445875 -0.0003088884 -0.0021797920
#> [4,] -8.298186e-05 -0.0003983308 -0.007951491 0.0005586363 -0.0002391215
#> [5,] -3.797603e-02 -0.0404707348 -0.597917282 0.0703908752 0.0750270535
#> [6,] -3.799992e-02 -0.0371638541 -0.388140282 0.0380613384 0.0369626454
#> [7,] -3.716385e-02 -0.0395400762 -0.528270621 0.0372504433 0.0393651494
#> [8,] -3.881403e-01 -0.5282706210 -0.719929653 0.3887917031 0.5296190334
#> [9,] 3.806134e-02 0.0372504433 0.388791703 -0.0710154527 -0.0696899316
#> [10,] 3.696265e-02 0.0393651494 0.529619033 -0.0696899316 -0.0737155779
#> [11,] 3.883582e-01 0.5289079300 0.719834715 -0.8523505456 -1.1452150083
#> [,11]
#> [1,] -0.606706604
#> [2,] 0.006671018
#> [3,] 0.002670955
#> [4,] 0.008298983
#> [5,] 1.293734767
#> [6,] 0.388358232
#> [7,] 0.528907930
#> [8,] 0.719834715
#> [9,] -0.852350546
#> [10,] -1.145215008
#> [11,] -1.607721760
#>
#> $jac_list[[9]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.041473955 -0.0314606247 -0.0168549181 -2.315242e-02 -0.015155127
#> [2,] -0.031460625 0.0538809583 0.0221715378 3.655728e-03 0.005427256
#> [3,] -0.016854918 0.0221715378 0.0558983063 -9.962610e-04 -0.007335694
#> [4,] -0.023152416 0.0036557279 -0.0009962610 3.814286e-02 0.004271949
#> [5,] -0.015155127 0.0054272559 -0.0073356944 4.271949e-03 0.024739070
#> [6,] -0.014696964 0.0039311657 -0.0056691003 -1.123568e-05 0.015484056
#> [7,] -0.013186167 0.0024647462 -0.0036293159 2.608542e-03 0.012322919
#> [8,] -0.006261574 0.0137271535 -0.0049091078 -3.313129e-03 0.005509252
#> [9,] 0.018453255 -0.0070166484 0.0002455213 -2.350538e-03 -0.027859077
#> [10,] 0.014008275 0.0005465727 0.0030723304 -6.571520e-03 -0.023077379
#> [11,] 0.004507730 -0.0020504007 0.0049401852 -3.219137e-03 -0.020306630
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -1.469696e-02 -0.013186167 -0.006261574 0.0184532547 0.0140082750
#> [2,] 3.931166e-03 0.002464746 0.013727153 -0.0070166484 0.0005465727
#> [3,] -5.669100e-03 -0.003629316 -0.004909108 0.0002455213 0.0030723304
#> [4,] -1.123568e-05 0.002608542 -0.003313129 -0.0023505380 -0.0065715199
#> [5,] 1.548406e-02 0.012322919 0.005509252 -0.0278590774 -0.0230773794
#> [6,] 3.916072e-03 0.014184771 0.435631005 -0.0039403723 -0.0138334905
#> [7,] 1.418477e-02 0.011665630 0.022251231 -0.0143350660 -0.0116250112
#> [8,] 4.356310e-01 0.022251231 0.108575188 -0.4352779847 -0.0209640014
#> [9,] -3.940372e-03 -0.014335066 -0.435277985 0.0083177316 0.0267726480
#> [10,] -1.383349e-02 -0.011625011 -0.020964001 0.0267726480 0.0233268429
#> [11,] -4.357096e-01 -0.022010417 -0.108751446 0.9189699565 0.0633575572
#> [,11]
#> [1,] 0.004507730
#> [2,] -0.002050401
#> [3,] 0.004940185
#> [4,] -0.003219137
#> [5,] -0.020306630
#> [6,] -0.435709562
#> [7,] -0.022010417
#> [8,] -0.108751446
#> [9,] 0.918969957
#> [10,] 0.063357557
#> [11,] 0.246113612
#>
#> $jac_list[[10]]
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.0475094828 -0.0400177827 -0.028260626 -0.034012882 -0.0080787157
#> [2,] -0.0400177827 0.0684544431 0.031820681 0.003857394 0.0065758994
#> [3,] -0.0282606263 0.0318206813 0.091939662 0.002503657 -0.0134695684
#> [4,] -0.0340128825 0.0038573936 0.002503657 0.053295287 0.0039965441
#> [5,] -0.0080787157 0.0065758994 -0.013469568 0.003996544 0.0125472134
#> [6,] -0.0070638919 0.0004634724 -0.004672035 0.005868902 0.0054358657
#> [7,] -0.0054458176 0.0014959299 -0.004698971 0.003207218 0.0049143464
#> [8,] -0.0008086081 0.0032326095 0.008125465 -0.006370958 0.0003637877
#> [9,] 0.0068928167 0.0013272395 0.007033868 -0.007504714 -0.0092578196
#> [10,] 0.0062173719 -0.0029139665 0.005195188 -0.003467928 -0.0090043526
#> [11,] -0.0110162084 0.0114643244 0.011169857 0.009527844 -0.0081867865
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] -0.0070638919 -0.005445818 -0.0008086081 0.006892817 0.006217372
#> [2,] 0.0004634724 0.001495930 0.0032326095 0.001327239 -0.002913966
#> [3,] -0.0046720350 -0.004698971 0.0081254648 0.007033868 0.005195188
#> [4,] 0.0058689018 0.003207218 -0.0063709584 -0.007504714 -0.003467928
#> [5,] 0.0054358657 0.004914346 0.0003637877 -0.009257820 -0.009004353
#> [6,] 0.0055361284 0.003344703 -0.0009680439 -0.005842292 -0.003635238
#> [7,] 0.0033447028 0.004126786 0.3172248172 -0.003525064 -0.004295150
#> [8,] -0.0009680439 0.317224817 -0.0604796319 0.001431173 -0.316729583
#> [9,] -0.0058422920 -0.003525064 0.0014311730 0.009950109 0.007200077
#> [10,] -0.0036352381 -0.004295150 -0.3167295835 0.007200077 0.009148932
#> [11,] 0.0008961357 -0.317074451 0.0602901594 0.008112522 0.703015362
#> [,11]
#> [1,] -0.0110162084
#> [2,] 0.0114643244
#> [3,] 0.0111698566
#> [4,] 0.0095278440
#> [5,] -0.0081867865
#> [6,] 0.0008961357
#> [7,] -0.3170744512
#> [8,] 0.0602901594
#> [9,] 0.0081125222
#> [10,] 0.7030153618
#> [11,] -0.1100765249
#>
#>
#> $theta_vcov
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 3.702524e-03 -1.215947e-04 -4.731168e-05 1.450739e-05 1.497878e-03
#> [2,] -1.215947e-04 4.166297e-03 5.181830e-06 -8.501705e-05 -2.892842e-03
#> [3,] -4.731168e-05 5.181830e-06 4.125814e-03 -1.641174e-05 -9.040069e-05
#> [4,] 1.450739e-05 -8.501705e-05 -1.641174e-05 3.954303e-03 1.872784e-04
#> [5,] 1.497878e-03 -2.892842e-03 -9.040069e-05 1.872784e-04 1.162924e-02
#> [6,] 9.528883e-04 -3.051437e-04 -1.464540e-03 1.037445e-04 1.171667e-03
#> [7,] -2.602792e-04 7.154405e-04 -1.610053e-04 -1.022748e-04 -8.342308e-04
#> [8,] 4.907597e-04 3.579757e-04 1.323707e-04 -1.731809e-03 -4.115907e-04
#> [9,] 2.835132e-05 1.522769e-04 -5.031469e-05 -5.113057e-06 -9.715561e-05
#> [10,] -7.267721e-05 -1.851224e-05 8.198068e-05 1.959919e-04 -1.454858e-04
#> [,6] [,7] [,8] [,9] [,10]
#> [1,] 0.0009528883 -0.0002602792 0.0004907597 2.835132e-05 -7.267721e-05
#> [2,] -0.0003051437 0.0007154405 0.0003579757 1.522769e-04 -1.851224e-05
#> [3,] -0.0014645400 -0.0001610053 0.0001323707 -5.031469e-05 8.198068e-05
#> [4,] 0.0001037445 -0.0001022748 -0.0017318089 -5.113057e-06 1.959919e-04
#> [5,] 0.0011716674 -0.0008342308 -0.0004115907 -9.715561e-05 -1.454858e-04
#> [6,] 0.0113483186 -0.0011633727 -0.0004920010 1.126993e-04 -1.244717e-04
#> [7,] -0.0011633727 0.0117530828 0.0003182121 -2.510208e-04 6.492154e-04
#> [8,] -0.0004920010 0.0003182121 0.0152793330 -2.440027e-03 1.085145e-03
#> [9,] 0.0001126993 -0.0002510208 -0.0024400268 9.713650e-03 -5.203255e-04
#> [10,] -0.0001244717 0.0006492154 0.0010851454 -5.203255e-04 1.123606e-02
#>
#> $full_frame
#> FEV1 RACE SEX ARMCD AVISIT USUBJID (weights)
#> 2 39.97105 Black or African American Female TRT VIS2 PT1 1
#> 4 20.48379 Black or African American Female TRT VIS4 PT1 1
#> 6 31.45522 Asian Male PBO VIS2 PT2 1
#> 7 36.87889 Asian Male PBO VIS3 PT2 1
#> 8 48.80809 Asian Male PBO VIS4 PT2 1
#> 10 35.98699 Black or African American Female PBO VIS2 PT3 1
#> 12 37.16444 Black or African American Female PBO VIS4 PT3 1
#> 13 33.89229 Asian Female TRT VIS1 PT4 1
#> 14 33.74637 Asian Female TRT VIS2 PT4 1
#> 16 54.45055 Asian Female TRT VIS4 PT4 1
#> 17 32.31386 Black or African American Male PBO VIS1 PT5 1
#> 19 46.79361 Black or African American Male PBO VIS3 PT5 1
#> 20 41.71154 Black or African American Male PBO VIS4 PT5 1
#> 23 39.02423 Black or African American Male PBO VIS3 PT6 1
#> 25 31.93050 Asian Female PBO VIS1 PT7 1
#> 26 32.90947 Asian Female PBO VIS2 PT7 1
#> 28 48.28031 Asian Female PBO VIS4 PT7 1
#> 29 32.23021 Black or African American Male PBO VIS1 PT8 1
#> 30 35.91080 Black or African American Male PBO VIS2 PT8 1
#> 31 45.54898 Black or African American Male PBO VIS3 PT8 1
#> 32 53.02877 Black or African American Male PBO VIS4 PT8 1
#> 33 47.16898 White Male TRT VIS1 PT9 1
#> 34 46.64287 White Male TRT VIS2 PT9 1
#> 36 58.09713 White Male TRT VIS4 PT9 1
#> 39 44.97613 Black or African American Female PBO VIS3 PT10 1
#> 41 44.32755 Asian Female TRT VIS1 PT11 1
#> 42 38.97813 Asian Female TRT VIS2 PT11 1
#> 43 43.72862 Asian Female TRT VIS3 PT11 1
#> 44 46.43393 Asian Female TRT VIS4 PT11 1
#> 45 40.34576 Asian Male PBO VIS1 PT12 1
#> 46 42.76568 Asian Male PBO VIS2 PT12 1
#> 47 40.11155 Asian Male PBO VIS3 PT12 1
#> 51 53.31791 White Male TRT VIS3 PT13 1
#> 52 56.07641 White Male TRT VIS4 PT13 1
#> 55 41.90837 Black or African American Male PBO VIS3 PT14 1
#> 59 34.65663 Asian Male PBO VIS3 PT15 1
#> 60 39.07791 Asian Male PBO VIS4 PT15 1
#> 62 35.89612 Asian Female PBO VIS2 PT16 1
#> 64 47.67264 Asian Female PBO VIS4 PT16 1
#> 65 22.65440 White Female PBO VIS1 PT17 1
#> 68 40.85376 White Female PBO VIS4 PT17 1
#> 69 32.60048 Asian Male TRT VIS1 PT18 1
#> 70 33.64329 Asian Male TRT VIS2 PT18 1
#> 72 40.92278 Asian Male TRT VIS4 PT18 1
#> 73 32.14831 Asian Male TRT VIS1 PT19 1
#> 74 46.43604 Asian Male TRT VIS2 PT19 1
#> 75 41.34973 Asian Male TRT VIS3 PT19 1
#> 76 66.30382 Asian Male TRT VIS4 PT19 1
#> 78 47.95358 White Female TRT VIS2 PT20 1
#> 79 53.97364 White Female TRT VIS3 PT20 1
#> 82 56.64544 White Male TRT VIS2 PT21 1
#> 83 49.70872 White Male TRT VIS3 PT21 1
#> 84 60.40497 White Male TRT VIS4 PT21 1
#> 85 45.98525 White Male TRT VIS1 PT22 1
#> 86 51.90911 White Male TRT VIS2 PT22 1
#> 87 41.50787 White Male TRT VIS3 PT22 1
#> 88 53.42727 White Male TRT VIS4 PT22 1
#> 89 23.86859 Black or African American Female PBO VIS1 PT23 1
#> 90 35.98563 Black or African American Female PBO VIS2 PT23 1
#> 91 43.60626 Black or African American Female PBO VIS3 PT23 1
#> 93 29.59773 White Female TRT VIS1 PT24 1
#> 94 35.50688 White Female TRT VIS2 PT24 1
#> 95 55.42944 White Female TRT VIS3 PT24 1
#> 96 52.10530 White Female TRT VIS4 PT24 1
#> 97 31.69644 White Female TRT VIS1 PT25 1
#> 98 32.16159 White Female TRT VIS2 PT25 1
#> 99 51.04735 White Female TRT VIS3 PT25 1
#> 100 55.85987 White Female TRT VIS4 PT25 1
#> 101 49.11706 White Female TRT VIS1 PT26 1
#> 102 49.25544 White Female TRT VIS2 PT26 1
#> 103 51.72211 White Female TRT VIS3 PT26 1
#> 104 69.99128 White Female TRT VIS4 PT26 1
#> 105 22.07169 Black or African American Female TRT VIS1 PT27 1
#> 107 46.08393 Black or African American Female TRT VIS3 PT27 1
#> 108 52.42288 Black or African American Female TRT VIS4 PT27 1
#> 109 37.69466 Black or African American Male TRT VIS1 PT28 1
#> 110 44.59400 Black or African American Male TRT VIS2 PT28 1
#> 111 52.08897 Black or African American Male TRT VIS3 PT28 1
#> 112 58.22961 Black or African American Male TRT VIS4 PT28 1
#> 113 37.22824 Black or African American Male TRT VIS1 PT29 1
#> 114 34.39863 Black or African American Male TRT VIS2 PT29 1
#> 116 36.34012 Black or African American Male TRT VIS4 PT29 1
#> 117 45.44182 Asian Female TRT VIS1 PT30 1
#> 118 41.54847 Asian Female TRT VIS2 PT30 1
#> 119 43.92172 Asian Female TRT VIS3 PT30 1
#> 120 61.83243 Asian Female TRT VIS4 PT30 1
#> 121 27.25656 Asian Female PBO VIS1 PT31 1
#> 123 45.65133 Asian Female PBO VIS3 PT31 1
#> 125 33.19334 Black or African American Male TRT VIS1 PT32 1
#> 128 41.66826 Black or African American Male TRT VIS4 PT32 1
#> 129 27.12753 Black or African American Male TRT VIS1 PT33 1
#> 130 31.74858 Black or African American Male TRT VIS2 PT33 1
#> 132 41.60000 Black or African American Male TRT VIS4 PT33 1
#> 133 39.45250 Asian Female PBO VIS1 PT34 1
#> 134 32.61823 Asian Female PBO VIS2 PT34 1
#> 135 34.62445 Asian Female PBO VIS3 PT34 1
#> 136 45.90515 Asian Female PBO VIS4 PT34 1
#> 137 36.17780 Black or African American Female TRT VIS1 PT35 1
#> 138 39.79796 Black or African American Female TRT VIS2 PT35 1
#> 140 50.08272 Black or African American Female TRT VIS4 PT35 1
#> 142 44.64316 Asian Female TRT VIS2 PT36 1
#> 144 39.73529 Asian Female TRT VIS4 PT36 1
#> 145 34.06164 White Female PBO VIS1 PT37 1
#> 146 40.18592 White Female PBO VIS2 PT37 1
#> 147 41.17584 White Female PBO VIS3 PT37 1
#> 148 57.76669 White Female PBO VIS4 PT37 1
#> 149 38.18460 Asian Female PBO VIS1 PT38 1
#> 151 47.19893 Asian Female PBO VIS3 PT38 1
#> 153 37.32785 Asian Female PBO VIS1 PT39 1
#> 155 43.16048 Asian Female PBO VIS3 PT39 1
#> 156 41.40349 Asian Female PBO VIS4 PT39 1
#> 157 30.15733 Black or African American Male PBO VIS1 PT40 1
#> 158 35.84353 Black or African American Male PBO VIS2 PT40 1
#> 159 40.95250 Black or African American Male PBO VIS3 PT40 1
#> 162 41.37928 Black or African American Male PBO VIS2 PT41 1
#> 163 50.17316 Black or African American Male PBO VIS3 PT41 1
#> 164 45.35226 Black or African American Male PBO VIS4 PT41 1
#> 165 39.06491 Black or African American Male PBO VIS1 PT42 1
#> 168 42.11960 Black or African American Male PBO VIS4 PT42 1
#> 169 29.81042 Black or African American Female TRT VIS1 PT43 1
#> 170 42.57055 Black or African American Female TRT VIS2 PT43 1
#> 171 47.81652 Black or African American Female TRT VIS3 PT43 1
#> 172 68.06024 Black or African American Female TRT VIS4 PT43 1
#> 173 35.62071 Black or African American Male TRT VIS1 PT44 1
#> 177 33.89134 Asian Female PBO VIS1 PT45 1
#> 178 36.42808 Asian Female PBO VIS2 PT45 1
#> 179 37.57519 Asian Female PBO VIS3 PT45 1
#> 180 58.46873 Asian Female PBO VIS4 PT45 1
#> 181 19.54516 Asian Male PBO VIS1 PT46 1
#> 182 31.13541 Asian Male PBO VIS2 PT46 1
#> 183 40.89955 Asian Male PBO VIS3 PT46 1
#> 185 22.18809 Asian Male TRT VIS1 PT47 1
#> 186 41.05857 Asian Male TRT VIS2 PT47 1
#> 187 37.32452 Asian Male TRT VIS3 PT47 1
#> 190 43.12432 Black or African American Male PBO VIS2 PT48 1
#> 191 41.99349 Black or African American Male PBO VIS3 PT48 1
#> 193 44.03080 White Female PBO VIS1 PT49 1
#> 194 38.66417 White Female PBO VIS2 PT49 1
#> 195 53.45993 White Female PBO VIS3 PT49 1
#> 197 29.81948 Asian Female TRT VIS1 PT50 1
#> 198 30.43859 Asian Female TRT VIS2 PT50 1
#> 199 40.18095 Asian Female TRT VIS3 PT50 1
#> 201 26.78578 Black or African American Female TRT VIS1 PT51 1
#> 202 34.55115 Black or African American Female TRT VIS2 PT51 1
#> 204 40.06421 Black or African American Female TRT VIS4 PT51 1
#> 206 43.09329 Black or African American Female TRT VIS2 PT52 1
#> 208 45.71567 Black or African American Female TRT VIS4 PT52 1
#> 209 40.74992 White Male PBO VIS1 PT53 1
#> 210 44.74635 White Male PBO VIS2 PT53 1
#> 217 40.14674 Asian Male TRT VIS1 PT55 1
#> 218 48.75859 Asian Male TRT VIS2 PT55 1
#> 219 46.43462 Asian Male TRT VIS3 PT55 1
#> 221 29.33990 Black or African American Male PBO VIS1 PT56 1
#> 224 47.93165 Black or African American Male PBO VIS4 PT56 1
#> 226 41.11632 Black or African American Male TRT VIS2 PT57 1
#> 227 47.05889 Black or African American Male TRT VIS3 PT57 1
#> 228 52.24599 Black or African American Male TRT VIS4 PT57 1
#> 230 54.14236 White Female TRT VIS2 PT58 1
#> 231 50.44618 White Female TRT VIS3 PT58 1
#> 233 37.53657 White Female TRT VIS1 PT59 1
#> 235 49.45840 White Female TRT VIS3 PT59 1
#> 236 59.12866 White Female TRT VIS4 PT59 1
#> 237 40.31268 Black or African American Female TRT VIS1 PT60 1
#> 238 39.66049 Black or African American Female TRT VIS2 PT60 1
#> 239 50.89726 Black or African American Female TRT VIS3 PT60 1
#> 240 56.13116 Black or African American Female TRT VIS4 PT60 1
#> 241 32.82981 Asian Male TRT VIS1 PT61 1
#> 242 46.53837 Asian Male TRT VIS2 PT61 1
#> 244 51.81265 Asian Male TRT VIS4 PT61 1
#> 246 29.91939 Asian Female PBO VIS2 PT62 1
#> 250 51.05656 White Female PBO VIS2 PT63 1
#> 251 50.50059 White Female PBO VIS3 PT63 1
#> 252 64.11388 White Female PBO VIS4 PT63 1
#> 253 32.21843 Black or African American Female PBO VIS1 PT64 1
#> 254 29.64732 Black or African American Female PBO VIS2 PT64 1
#> 256 45.09919 Black or African American Female PBO VIS4 PT64 1
#> 257 39.75659 Asian Female TRT VIS1 PT65 1
#> 258 37.28894 Asian Female TRT VIS2 PT65 1
#> 259 44.80145 Asian Female TRT VIS3 PT65 1
#> 260 65.95920 Asian Female TRT VIS4 PT65 1
#> 261 33.43439 Asian Male TRT VIS1 PT66 1
#> 262 33.57042 Asian Male TRT VIS2 PT66 1
#> 263 39.91543 Asian Male TRT VIS3 PT66 1
#> 264 49.57098 Asian Male TRT VIS4 PT66 1
#> 265 38.91634 White Female TRT VIS1 PT67 1
#> 266 36.69011 White Female TRT VIS2 PT67 1
#> 267 45.66665 White Female TRT VIS3 PT67 1
#> 268 52.07431 White Female TRT VIS4 PT67 1
#> 269 42.21411 White Female TRT VIS1 PT68 1
#> 270 45.02901 White Female TRT VIS2 PT68 1
#> 273 30.98338 Black or African American Male PBO VIS1 PT69 1
#> 274 44.72932 Black or African American Male PBO VIS2 PT69 1
#> 275 40.68711 Black or African American Male PBO VIS3 PT69 1
#> 276 34.71530 Black or African American Male PBO VIS4 PT69 1
#> 277 27.30752 Black or African American Male PBO VIS1 PT70 1
#> 278 37.31585 Black or African American Male PBO VIS2 PT70 1
#> 280 44.83000 Black or African American Male PBO VIS4 PT70 1
#> 281 32.93042 Asian Male TRT VIS1 PT71 1
#> 282 44.91911 Asian Male TRT VIS2 PT71 1
#> 283 45.68636 Asian Male TRT VIS3 PT71 1
#> 284 65.98800 Asian Male TRT VIS4 PT71 1
#> 285 46.60130 Asian Female TRT VIS1 PT72 1
#> 286 40.89786 Asian Female TRT VIS2 PT72 1
#> 287 46.66708 Asian Female TRT VIS3 PT72 1
#> 291 43.83270 White Male PBO VIS3 PT73 1
#> 292 44.11604 White Male PBO VIS4 PT73 1
#> 293 38.29612 White Female PBO VIS1 PT74 1
#> 295 51.38570 White Female PBO VIS3 PT74 1
#> 296 56.20979 White Female PBO VIS4 PT74 1
#> 298 43.45819 White Male PBO VIS2 PT75 1
#> 299 38.38741 White Male PBO VIS3 PT75 1
#> 300 56.42818 White Male PBO VIS4 PT75 1
#> 301 39.05050 White Male TRT VIS1 PT76 1
#> 304 54.09200 White Male TRT VIS4 PT76 1
#> 305 31.40521 Asian Male TRT VIS1 PT77 1
#> 306 46.13330 Asian Male TRT VIS2 PT77 1
#> 307 45.29845 Asian Male TRT VIS3 PT77 1
#> 308 28.06936 Asian Male TRT VIS4 PT77 1
#> 310 42.50283 White Female TRT VIS2 PT78 1
#> 311 46.45368 White Female TRT VIS3 PT78 1
#> 312 64.97366 White Female TRT VIS4 PT78 1
#> 316 43.97847 Asian Female PBO VIS4 PT79 1
#> 317 35.33466 Asian Male TRT VIS1 PT80 1
#> 318 39.34378 Asian Male TRT VIS2 PT80 1
#> 319 41.27633 Asian Male TRT VIS3 PT80 1
#> 322 39.83058 White Male PBO VIS2 PT81 1
#> 323 43.49673 White Male PBO VIS3 PT81 1
#> 324 44.06114 White Male PBO VIS4 PT81 1
#> 325 41.43742 Black or African American Female PBO VIS1 PT82 1
#> 327 46.16954 Black or African American Female PBO VIS3 PT82 1
#> 328 54.24024 Black or African American Female PBO VIS4 PT82 1
#> 329 36.61831 White Male TRT VIS1 PT83 1
#> 330 42.09272 White Male TRT VIS2 PT83 1
#> 331 50.69556 White Male TRT VIS3 PT83 1
#> 332 51.72563 White Male TRT VIS4 PT83 1
#> 336 53.89947 Asian Female PBO VIS4 PT84 1
#> 339 39.94420 Asian Female PBO VIS3 PT85 1
#> 340 56.42482 Asian Female PBO VIS4 PT85 1
#> 341 41.86385 Black or African American Female TRT VIS1 PT86 1
#> 342 34.56420 Black or African American Female TRT VIS2 PT86 1
#> 343 38.68927 Black or African American Female TRT VIS3 PT86 1
#> 344 62.88743 Black or African American Female TRT VIS4 PT86 1
#> 345 28.85343 White Male PBO VIS1 PT87 1
#> 347 49.29495 White Male PBO VIS3 PT87 1
#> 349 28.74029 Black or African American Female PBO VIS1 PT88 1
#> 351 43.59994 Black or African American Female PBO VIS3 PT88 1
#> 352 57.38616 Black or African American Female PBO VIS4 PT88 1
#> 353 35.36824 Black or African American Male PBO VIS1 PT89 1
#> 354 43.06110 Black or African American Male PBO VIS2 PT89 1
#> 355 31.27551 Black or African American Male PBO VIS3 PT89 1
#> 356 54.13245 Black or African American Male PBO VIS4 PT89 1
#> 357 25.97050 Asian Male PBO VIS1 PT90 1
#> 363 51.17493 White Female TRT VIS3 PT91 1
#> 364 48.44043 White Female TRT VIS4 PT91 1
#> 365 43.33128 White Female TRT VIS1 PT92 1
#> 367 55.93546 White Female TRT VIS3 PT92 1
#> 368 54.15312 White Female TRT VIS4 PT92 1
#> 370 40.60252 Black or African American Male PBO VIS2 PT93 1
#> 371 44.44715 Black or African American Male PBO VIS3 PT93 1
#> 372 40.54161 Black or African American Male PBO VIS4 PT93 1
#> 373 33.95563 Asian Female PBO VIS1 PT94 1
#> 375 43.67802 Asian Female PBO VIS3 PT94 1
#> 376 42.76023 Asian Female PBO VIS4 PT94 1
#> 378 42.82678 Asian Female PBO VIS2 PT95 1
#> 379 39.59218 Asian Female PBO VIS3 PT95 1
#> 381 33.49216 Black or African American Female PBO VIS1 PT96 1
#> 382 35.39266 Black or African American Female PBO VIS2 PT96 1
#> 384 42.36266 Black or African American Female PBO VIS4 PT96 1
#> 385 48.54368 White Male TRT VIS1 PT97 1
#> 386 43.94366 White Male TRT VIS2 PT97 1
#> 388 47.91204 White Male TRT VIS4 PT97 1
#> 389 20.72928 Asian Male PBO VIS1 PT98 1
#> 390 28.00599 Asian Male PBO VIS2 PT98 1
#> 391 40.19255 Asian Male PBO VIS3 PT98 1
#> 392 37.79360 Asian Male PBO VIS4 PT98 1
#> 394 36.75177 Black or African American Male PBO VIS2 PT99 1
#> 397 34.59822 Black or African American Female PBO VIS1 PT100 1
#> 398 39.32034 Black or African American Female PBO VIS2 PT100 1
#> 399 40.65702 Black or African American Female PBO VIS3 PT100 1
#> 402 43.03255 White Male TRT VIS2 PT101 1
#> 403 54.65715 White Male TRT VIS3 PT101 1
#> 405 35.55742 Asian Female PBO VIS1 PT102 1
#> 406 43.70215 Asian Female PBO VIS2 PT102 1
#> 407 42.52157 Asian Female PBO VIS3 PT102 1
#> 408 54.89337 Asian Female PBO VIS4 PT102 1
#> 409 32.03460 Asian Female PBO VIS1 PT103 1
#> 410 29.45107 Asian Female PBO VIS2 PT103 1
#> 411 45.35138 Asian Female PBO VIS3 PT103 1
#> 413 38.73784 Black or African American Female PBO VIS1 PT104 1
#> 415 41.42283 Black or African American Female PBO VIS3 PT104 1
#> 416 47.32385 Black or African American Female PBO VIS4 PT104 1
#> 418 47.55310 Black or African American Female TRT VIS2 PT105 1
#> 419 49.06509 Black or African American Female TRT VIS3 PT105 1
#> 421 29.22591 Asian Female TRT VIS1 PT106 1
#> 422 40.08175 Asian Female TRT VIS2 PT106 1
#> 423 45.68142 Asian Female TRT VIS3 PT106 1
#> 424 41.47403 Asian Female TRT VIS4 PT106 1
#> 427 42.51970 White Female PBO VIS3 PT107 1
#> 428 69.36099 White Female PBO VIS4 PT107 1
#> 429 42.39760 White Male TRT VIS1 PT108 1
#> 430 43.72376 White Male TRT VIS2 PT108 1
#> 431 49.47601 White Male TRT VIS3 PT108 1
#> 432 51.94188 White Male TRT VIS4 PT108 1
#> 434 40.59100 Black or African American Female PBO VIS2 PT109 1
#> 435 39.97833 Black or African American Female PBO VIS3 PT109 1
#> 436 31.69049 Black or African American Female PBO VIS4 PT109 1
#> 438 37.20517 Asian Male TRT VIS2 PT110 1
#> 439 46.28740 Asian Male TRT VIS3 PT110 1
#> 444 41.58720 White Female PBO VIS4 PT111 1
#> 445 32.17365 Black or African American Female PBO VIS1 PT112 1
#> 447 40.69375 Black or African American Female PBO VIS3 PT112 1
#> 449 32.28771 Asian Male PBO VIS1 PT113 1
#> 450 41.76205 Asian Male PBO VIS2 PT113 1
#> 451 40.06768 Asian Male PBO VIS3 PT113 1
#> 453 29.14213 Black or African American Male PBO VIS1 PT114 1
#> 454 39.50989 Black or African American Male PBO VIS2 PT114 1
#> 455 43.32349 Black or African American Male PBO VIS3 PT114 1
#> 456 47.16756 Black or African American Male PBO VIS4 PT114 1
#> 457 40.93020 Asian Female PBO VIS1 PT115 1
#> 458 42.19406 Asian Female PBO VIS2 PT115 1
#> 459 41.21057 Asian Female PBO VIS3 PT115 1
#> 461 38.54330 Black or African American Male TRT VIS1 PT116 1
#> 463 43.96324 Black or African American Male TRT VIS3 PT116 1
#> 464 42.67652 Black or African American Male TRT VIS4 PT116 1
#> 465 22.79584 Black or African American Male PBO VIS1 PT117 1
#> 469 31.43559 Asian Female PBO VIS1 PT118 1
#> 470 38.85064 Asian Female PBO VIS2 PT118 1
#> 471 48.24288 Asian Female PBO VIS3 PT118 1
#> 473 44.71302 White Male TRT VIS1 PT119 1
#> 474 51.85370 White Male TRT VIS2 PT119 1
#> 477 30.56757 Asian Female PBO VIS1 PT120 1
#> 484 59.90473 Black or African American Male TRT VIS4 PT121 1
#> 487 49.76150 Asian Female PBO VIS3 PT122 1
#> 489 47.21985 White Female PBO VIS1 PT123 1
#> 490 40.34525 White Female PBO VIS2 PT123 1
#> 491 48.29793 White Female PBO VIS3 PT123 1
#> 494 44.39634 Asian Female TRT VIS2 PT124 1
#> 495 41.71421 Asian Female TRT VIS3 PT124 1
#> 496 47.37535 Asian Female TRT VIS4 PT124 1
#> 497 42.03797 White Male PBO VIS1 PT125 1
#> 498 37.56100 White Male PBO VIS2 PT125 1
#> 499 45.11793 White Male PBO VIS3 PT125 1
#> 501 34.62530 Asian Male TRT VIS1 PT126 1
#> 502 45.28206 Asian Male TRT VIS2 PT126 1
#> 504 63.57761 Asian Male TRT VIS4 PT126 1
#> 505 35.80878 Black or African American Female TRT VIS1 PT127 1
#> 508 52.67314 Black or African American Female TRT VIS4 PT127 1
#> 509 35.88734 Asian Female TRT VIS1 PT128 1
#> 510 38.73222 Asian Female TRT VIS2 PT128 1
#> 511 46.70361 Asian Female TRT VIS3 PT128 1
#> 512 53.65398 Asian Female TRT VIS4 PT128 1
#> 513 36.71543 White Male TRT VIS1 PT129 1
#> 518 41.54317 White Male PBO VIS2 PT130 1
#> 519 51.67909 White Male PBO VIS3 PT130 1
#> 521 27.40130 Asian Female PBO VIS1 PT131 1
#> 522 30.33517 Asian Female PBO VIS2 PT131 1
#> 523 37.73092 Asian Female PBO VIS3 PT131 1
#> 524 29.11668 Asian Female PBO VIS4 PT131 1
#> 526 32.08830 Asian Male PBO VIS2 PT132 1
#> 527 41.66067 Asian Male PBO VIS3 PT132 1
#> 528 53.90815 Asian Male PBO VIS4 PT132 1
#> 530 35.06937 White Male PBO VIS2 PT133 1
#> 531 47.17615 White Male PBO VIS3 PT133 1
#> 532 56.49347 White Male PBO VIS4 PT133 1
#> 534 38.88006 Black or African American Male PBO VIS2 PT134 1
#> 535 47.54070 Black or African American Male PBO VIS3 PT134 1
#> 536 43.53705 Black or African American Male PBO VIS4 PT134 1
#> 537 31.82054 Black or African American Male PBO VIS1 PT135 1
#> 538 39.62816 Black or African American Male PBO VIS2 PT135 1
#> 539 44.95543 Black or African American Male PBO VIS3 PT135 1
#> 540 21.11543 Black or African American Male PBO VIS4 PT135 1
#> 541 34.74671 White Female TRT VIS1 PT136 1
#> 544 56.69249 White Female TRT VIS4 PT136 1
#> 545 22.73126 Asian Female TRT VIS1 PT137 1
#> 546 32.50075 Asian Female TRT VIS2 PT137 1
#> 547 42.37206 Asian Female TRT VIS3 PT137 1
#> 548 42.89847 Asian Female TRT VIS4 PT137 1
#> 549 55.62582 Asian Male TRT VIS1 PT138 1
#> 550 45.38998 Asian Male TRT VIS2 PT138 1
#> 551 52.66743 Asian Male TRT VIS3 PT138 1
#> 555 34.18931 Asian Female TRT VIS3 PT139 1
#> 556 45.59740 Asian Female TRT VIS4 PT139 1
#> 557 28.89198 Black or African American Female PBO VIS1 PT140 1
#> 558 38.46147 Black or African American Female PBO VIS2 PT140 1
#> 560 49.90357 Black or African American Female PBO VIS4 PT140 1
#> 562 44.14167 White Male TRT VIS2 PT141 1
#> 564 55.24278 White Male TRT VIS4 PT141 1
#> 569 27.38001 Black or African American Female TRT VIS1 PT143 1
#> 570 33.63251 Black or African American Female TRT VIS2 PT143 1
#> 572 39.34410 Black or African American Female TRT VIS4 PT143 1
#> 573 26.98575 Asian Female PBO VIS1 PT144 1
#> 574 24.04175 Asian Female PBO VIS2 PT144 1
#> 575 42.16648 Asian Female PBO VIS3 PT144 1
#> 576 44.75380 Asian Female PBO VIS4 PT144 1
#> 577 31.55469 Black or African American Male PBO VIS1 PT145 1
#> 578 44.42696 Black or African American Male PBO VIS2 PT145 1
#> 579 44.10343 Black or African American Male PBO VIS3 PT145 1
#> 582 37.87445 Asian Female TRT VIS2 PT146 1
#> 583 48.31828 Asian Female TRT VIS3 PT146 1
#> 584 50.21520 Asian Female TRT VIS4 PT146 1
#> 585 41.94615 Asian Female PBO VIS1 PT147 1
#> 586 39.62690 Asian Female PBO VIS2 PT147 1
#> 587 46.69763 Asian Female PBO VIS3 PT147 1
#> 590 43.75255 Black or African American Male TRT VIS2 PT148 1
#> 591 47.38873 Black or African American Male TRT VIS3 PT148 1
#> 593 32.43412 Asian Female PBO VIS1 PT149 1
#> 594 43.07163 Asian Female PBO VIS2 PT149 1
#> 595 42.99551 Asian Female PBO VIS3 PT149 1
#> 596 53.82759 Asian Female PBO VIS4 PT149 1
#> 599 50.64802 White Male PBO VIS3 PT150 1
#> 600 63.44051 White Male PBO VIS4 PT150 1
#> 601 34.48949 Asian Female PBO VIS1 PT151 1
#> 602 40.08056 Asian Female PBO VIS2 PT151 1
#> 604 47.46553 Asian Female PBO VIS4 PT151 1
#> 606 37.11697 Asian Female TRT VIS2 PT152 1
#> 608 36.25120 Asian Female TRT VIS4 PT152 1
#> 609 29.20171 Black or African American Male PBO VIS1 PT153 1
#> 610 31.53773 Black or African American Male PBO VIS2 PT153 1
#> 611 42.35683 Black or African American Male PBO VIS3 PT153 1
#> 612 64.78352 Black or African American Male PBO VIS4 PT153 1
#> 613 32.72757 Black or African American Female PBO VIS1 PT154 1
#> 614 37.50022 Black or African American Female PBO VIS2 PT154 1
#> 616 57.03861 Black or African American Female PBO VIS4 PT154 1
#> 617 36.32475 Asian Male TRT VIS1 PT155 1
#> 619 41.46725 Asian Male TRT VIS3 PT155 1
#> 620 59.01411 Asian Male TRT VIS4 PT155 1
#> 621 30.14970 White Male PBO VIS1 PT156 1
#> 622 34.91740 White Male PBO VIS2 PT156 1
#> 623 52.13900 White Male PBO VIS3 PT156 1
#> 624 58.73839 White Male PBO VIS4 PT156 1
#> 625 35.83185 Black or African American Male TRT VIS1 PT157 1
#> 628 56.41409 Black or African American Male TRT VIS4 PT157 1
#> 630 43.55593 Black or African American Male TRT VIS2 PT158 1
#> 631 44.26320 Black or African American Male TRT VIS3 PT158 1
#> 632 59.25579 Black or African American Male TRT VIS4 PT158 1
#> 633 28.47314 Asian Female TRT VIS1 PT159 1
#> 634 47.47581 Asian Female TRT VIS2 PT159 1
#> 638 46.47483 Asian Male TRT VIS2 PT160 1
#> 639 51.22677 Asian Male TRT VIS3 PT160 1
#> 640 45.82777 Asian Male TRT VIS4 PT160 1
#> 642 39.06783 Black or African American Female PBO VIS2 PT161 1
#> 645 29.99542 Asian Male PBO VIS1 PT162 1
#> 648 54.17796 Asian Male PBO VIS4 PT162 1
#> 650 44.55743 White Male PBO VIS2 PT163 1
#> 652 62.59579 White Male PBO VIS4 PT163 1
#> 654 35.48396 Black or African American Female PBO VIS2 PT164 1
#> 655 44.07768 Black or African American Female PBO VIS3 PT164 1
#> 656 46.57837 Black or African American Female PBO VIS4 PT164 1
#> 657 47.67979 White Female TRT VIS1 PT165 1
#> 661 22.15439 Asian Male TRT VIS1 PT166 1
#> 665 34.27765 Black or African American Male PBO VIS1 PT167 1
#> 666 36.90059 Black or African American Male PBO VIS2 PT167 1
#> 668 40.54285 Black or African American Male PBO VIS4 PT167 1
#> 669 29.09494 Black or African American Female PBO VIS1 PT168 1
#> 670 37.21768 Black or African American Female PBO VIS2 PT168 1
#> 671 43.08491 Black or African American Female PBO VIS3 PT168 1
#> 673 27.12174 White Female PBO VIS1 PT169 1
#> 674 34.11916 White Female PBO VIS2 PT169 1
#> 678 40.80230 White Female TRT VIS2 PT170 1
#> 679 45.89269 White Female TRT VIS3 PT170 1
#> 680 43.69153 White Female TRT VIS4 PT170 1
#> 682 29.22869 Asian Female PBO VIS2 PT171 1
#> 684 55.68362 Asian Female PBO VIS4 PT171 1
#> 685 31.90698 Asian Female TRT VIS1 PT172 1
#> 686 37.31061 Asian Female TRT VIS2 PT172 1
#> 687 40.75546 Asian Female TRT VIS3 PT172 1
#> 689 42.19474 White Female TRT VIS1 PT173 1
#> 690 44.87228 White Female TRT VIS2 PT173 1
#> 691 47.55198 White Female TRT VIS3 PT173 1
#> 693 50.62894 Black or African American Female TRT VIS1 PT174 1
#> 694 45.47551 Black or African American Female TRT VIS2 PT174 1
#> 695 48.62168 Black or African American Female TRT VIS3 PT174 1
#> 697 29.66493 Black or African American Female PBO VIS1 PT175 1
#> 698 34.57406 Black or African American Female PBO VIS2 PT175 1
#> 700 38.11676 Black or African American Female PBO VIS4 PT175 1
#> 701 33.77204 Black or African American Male TRT VIS1 PT176 1
#> 702 34.26148 Black or African American Male TRT VIS2 PT176 1
#> 704 58.81037 Black or African American Male TRT VIS4 PT176 1
#> 707 39.88119 Black or African American Male PBO VIS3 PT177 1
#> 709 31.62708 Black or African American Male PBO VIS1 PT178 1
#> 712 48.22049 Black or African American Male PBO VIS4 PT178 1
#> 713 42.58829 White Male TRT VIS1 PT179 1
#> 715 49.33262 White Male TRT VIS3 PT179 1
#> 716 53.74331 White Male TRT VIS4 PT179 1
#> 717 29.71857 Asian Male PBO VIS1 PT180 1
#> 718 30.45651 Asian Male PBO VIS2 PT180 1
#> 719 38.29800 Asian Male PBO VIS3 PT180 1
#> 721 36.81040 Asian Female PBO VIS1 PT181 1
#> 723 42.35045 Asian Female PBO VIS3 PT181 1
#> 724 39.39860 Asian Female PBO VIS4 PT181 1
#> 727 49.73629 Black or African American Female TRT VIS3 PT182 1
#> 728 41.58082 Black or African American Female TRT VIS4 PT182 1
#> 729 43.58901 Black or African American Female TRT VIS1 PT183 1
#> 730 40.16762 Black or African American Female TRT VIS2 PT183 1
#> 734 41.08206 White Female TRT VIS2 PT184 1
#> 736 69.37409 White Female TRT VIS4 PT184 1
#> 738 41.27625 Black or African American Female PBO VIS2 PT185 1
#> 739 44.76138 Black or African American Female PBO VIS3 PT185 1
#> 740 39.69815 Black or African American Female PBO VIS4 PT185 1
#> 741 38.44296 White Male PBO VIS1 PT186 1
#> 742 48.20586 White Male PBO VIS2 PT186 1
#> 744 35.50735 White Male PBO VIS4 PT186 1
#> 745 32.08153 Black or African American Female PBO VIS1 PT187 1
#> 749 44.69256 Black or African American Female PBO VIS1 PT188 1
#> 751 42.18689 Black or African American Female PBO VIS3 PT188 1
#> 753 37.01741 Asian Female TRT VIS1 PT189 1
#> 754 38.26920 Asian Female TRT VIS2 PT189 1
#> 755 49.28806 Asian Female TRT VIS3 PT189 1
#> 757 40.45953 Black or African American Female TRT VIS1 PT190 1
#> 758 45.10337 Black or African American Female TRT VIS2 PT190 1
#> 759 45.58250 Black or African American Female TRT VIS3 PT190 1
#> 760 62.96989 Black or African American Female TRT VIS4 PT190 1
#> 761 30.78252 White Male TRT VIS1 PT191 1
#> 764 44.69667 White Male TRT VIS4 PT191 1
#> 765 32.72491 White Female TRT VIS1 PT192 1
#> 766 45.78702 White Female TRT VIS2 PT192 1
#> 767 48.74886 White Female TRT VIS3 PT192 1
#> 768 84.08449 White Female TRT VIS4 PT192 1
#> 770 30.19495 Asian Male PBO VIS2 PT193 1
#> 771 36.78573 Asian Male PBO VIS3 PT193 1
#> 772 61.03588 Asian Male PBO VIS4 PT193 1
#> 773 20.36749 Black or African American Male PBO VIS1 PT194 1
#> 774 35.22480 Black or African American Male PBO VIS2 PT194 1
#> 775 37.42847 Black or African American Male PBO VIS3 PT194 1
#> 776 30.20501 Black or African American Male PBO VIS4 PT194 1
#> 778 49.12862 White Female TRT VIS2 PT195 1
#> 779 47.31234 White Female TRT VIS3 PT195 1
#> 781 19.28388 Asian Male PBO VIS1 PT196 1
#> 782 30.00682 Asian Male PBO VIS2 PT196 1
#> 784 49.21768 Asian Male PBO VIS4 PT196 1
#> 788 40.13353 Black or African American Male PBO VIS4 PT197 1
#> 789 42.34534 Black or African American Male TRT VIS1 PT198 1
#> 790 52.32575 Black or African American Male TRT VIS2 PT198 1
#> 792 69.26254 Black or African American Male TRT VIS4 PT198 1
#> 797 35.70341 Black or African American Male PBO VIS1 PT200 1
#> 798 41.64454 Black or African American Male PBO VIS2 PT200 1
#> 800 54.25081 Black or African American Male PBO VIS4 PT200 1
#>
#> $xlev
#> $xlev$RACE
#> [1] "Asian" "Black or African American"
#> [3] "White"
#>
#> $xlev$SEX
#> [1] "Male" "Female"
#>
#> $xlev$ARMCD
#> [1] "PBO" "TRT"
#>
#> $xlev$AVISIT
#> [1] "VIS1" "VIS2" "VIS3" "VIS4"
#>
#>
#> $contrasts
#> $contrasts$RACE
#> Black or African American White
#> Asian 0 0
#> Black or African American 1 0
#> White 0 1
#>
#> $contrasts$SEX
#> Female
#> Male 0
#> Female 1
#>
#> $contrasts$ARMCD
#> TRT
#> PBO 0
#> TRT 1
#>
#> $contrasts$AVISIT
#> VIS2 VIS3 VIS4
#> VIS1 0 0 0
#> VIS2 1 0 0
#> VIS3 0 1 0
#> VIS4 0 0 1
#>
#>
# Get convergence code and message.
component(fit, c("convergence", "conv_message"))
#> $convergence
#> [1] 0
#>
#> $conv_message
#> [1] "CONVERGENCE: REL_REDUCTION_OF_F <= FACTR*EPSMCH"
#>
# Get modeled formula as a string.
component(fit, c("formula"))
#> [1] "FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID)"