![[Experimental]](figures/lifecycle-experimental.svg)
Usage
# S3 method for mmrm_tmb
coef(object, complete = TRUE, ...)
# S3 method for mmrm_tmb
fitted(object, ...)
# S3 method for mmrm_tmb
model.frame(formula, exclude = "subject_var", full, ...)
# S3 method for mmrm_tmb
logLik(object, ...)
# S3 method for mmrm_tmb
formula(x, ...)
# S3 method for mmrm_tmb
vcov(object, complete = TRUE, ...)
# S3 method for mmrm_tmb
VarCorr(x, sigma = NA, ...)
# S3 method for mmrm_tmb
deviance(object, ...)
# S3 method for mmrm_tmb
AIC(object, corrected = FALSE, ..., k = 2)
# S3 method for mmrm_tmb
BIC(object, ...)
# S3 method for mmrm_tmb
print(x, ...)
# S3 method for mmrm_tmb
residuals(object, type = c("response", "pearson", "normalized"), ...)Arguments
- object
(
mmrm_tmb)
the fitted MMRM object.- complete
(
flag)
whether to include potential non-estimable coefficients.- ...
not used.
- formula
(
mmrm_tmb)
same asobject.- exclude
(
character)
names of variable to exclude.- full
(
flag) indicator whether to return full model frame (deprecated).- x
(
mmrm_tmb)
same asobject.- sigma
cannot be used (this parameter does not exist in MMRM).
- corrected
(
flag)
whether corrected AIC should be calculated.- k
(
number)
the penalty per parameter to be used; defaultk = 2is the classical AIC.- type
(
string)
unscaled (response),pearsonornormalized. Default isresponse, and this is the only type available for use with models with a spatial covariance structure.
Details
exclude argument controls the variables the returned model frame will exclude.
Possible options are "subject_var", "visit_var" and "group_var", representing the
subject variable, visit variable or group variable.
Functions
coef(mmrm_tmb): obtains the estimated coefficients.fitted(mmrm_tmb): obtains the fitted values.model.frame(mmrm_tmb): obtains the model frame.logLik(mmrm_tmb): obtains the attained log likelihood value.formula(mmrm_tmb): obtains the used formula.vcov(mmrm_tmb): obtains the variance-covariance matrix estimate for the coefficients.VarCorr(mmrm_tmb): obtains the variance-covariance matrix estimate for the residuals.deviance(mmrm_tmb): obtains the deviance, which is defined here as twice the negative log likelihood, which can either be integrated over the coefficients for REML fits or the usual one for ML fits.AIC(mmrm_tmb): obtains the Akaike Information Criterion, where the degrees of freedom are the number of variance parameters (n_theta). Ifcorrected, then this is multiplied withm / (m - n_theta - 1)wheremis the number of observations minus the number of coefficients, orn_theta + 2if it is smaller than that (Hurvich and Tsai 1989; Burnham and Anderson 1998) .BIC(mmrm_tmb): obtains the Bayesian Information Criterion, which is using the natural logarithm of the number of subjects for the penalty parameterk.print(mmrm_tmb): prints the object.residuals(mmrm_tmb): to obtain residuals - either unscaled ('response'), 'pearson' or 'normalized'.
References
Hurvich CM, Tsai C (1989). “Regression and time series model selection in small samples.” Biometrika, 76(2), 297--307. doi:10.2307/2336663 .
Burnham KP, Anderson DR (1998). “Practical use of the information-theoretic approach.” In Model selection and inference, 75--117. Springer. doi:10.1007/978-1-4757-2917-7_3 .
Gałecki A, Burzykowski T (2013). “Linear mixed-effects model.” In Linear mixed-effects models using R, 245--273. Springer.
Examples
formula <- FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID)
object <- fit_mmrm(formula, fev_data, weights = rep(1, nrow(fev_data)))
# Estimated coefficients:
coef(object)
#> (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
# Fitted values:
fitted(object)
#> 2 4 6 7 8 10 12 13
#> 41.20593 52.08639 35.61706 41.11959 45.83137 37.47363 47.68794 34.87777
#> 14 16 17 19 20 23 25 26
#> 39.67543 50.55589 32.30798 42.65009 47.36187 42.65009 31.10354 35.94313
#> 28 29 30 31 32 33 34 36
#> 46.15744 32.30798 37.14756 42.65009 47.36187 40.19527 44.99293 55.87340
#> 39 41 42 43 44 45 46 47
#> 42.97615 34.87777 39.67543 44.52619 50.55589 30.77748 35.61706 41.11959
#> 51 52 55 59 60 62 64 65
#> 49.84370 55.87340 42.65009 41.11959 45.83137 35.94313 46.15744 36.74710
#> 68 69 70 72 73 74 75 76
#> 51.80100 34.55171 39.34937 50.22983 34.55171 39.34937 44.20013 50.22983
#> 78 79 82 83 84 85 86 87
#> 45.31900 50.16976 44.99293 49.84370 55.87340 40.19527 44.99293 49.84370
#> 88 89 90 91 93 94 95 96
#> 55.87340 32.63404 37.47363 42.97615 40.52133 45.31900 50.16976 56.19946
#> 97 98 99 100 101 102 103 104
#> 40.52133 45.31900 50.16976 56.19946 40.52133 45.31900 50.16976 56.19946
#> 105 107 108 109 110 111 112 113
#> 36.40827 46.05669 52.08639 36.08221 40.87987 45.73063 51.76033 36.08221
#> 114 116 117 118 119 120 121 123
#> 40.87987 51.76033 34.87777 39.67543 44.52619 50.55589 31.10354 41.44565
#> 125 128 129 130 132 133 134 135
#> 36.08221 51.76033 36.08221 40.87987 51.76033 31.10354 35.94313 41.44565
#> 136 137 138 140 142 144 145 146
#> 46.15744 36.40827 41.20593 52.08639 39.67543 50.55589 36.74710 41.58669
#> 147 148 149 151 153 155 156 157
#> 47.08922 51.80100 31.10354 41.44565 31.10354 41.44565 46.15744 32.30798
#> 158 159 162 163 164 165 168 169
#> 37.14756 42.65009 37.14756 42.65009 47.36187 32.30798 47.36187 36.40827
#> 170 171 172 173 177 178 179 180
#> 41.20593 46.05669 52.08639 36.08221 31.10354 35.94313 41.44565 46.15744
#> 181 182 183 185 186 187 190 191
#> 30.77748 35.61706 41.11959 34.55171 39.34937 44.20013 37.14756 42.65009
#> 193 194 195 197 198 199 201 202
#> 36.74710 41.58669 47.08922 34.87777 39.67543 44.52619 36.40827 41.20593
#> 204 206 208 209 210 217 218 219
#> 52.08639 41.20593 52.08639 36.42104 41.26063 34.55171 39.34937 44.20013
#> 221 224 226 227 228 230 231 233
#> 32.30798 47.36187 40.87987 45.73063 51.76033 45.31900 50.16976 40.52133
#> 235 236 237 238 239 240 241 242
#> 50.16976 56.19946 36.40827 41.20593 46.05669 52.08639 34.55171 39.34937
#> 244 246 250 251 252 253 254 256
#> 50.22983 35.94313 41.58669 47.08922 51.80100 32.63404 37.47363 47.68794
#> 257 258 259 260 261 262 263 264
#> 34.87777 39.67543 44.52619 50.55589 34.55171 39.34937 44.20013 50.22983
#> 265 266 267 268 269 270 273 274
#> 40.52133 45.31900 50.16976 56.19946 40.52133 45.31900 32.30798 37.14756
#> 275 276 277 278 280 281 282 283
#> 42.65009 47.36187 32.30798 37.14756 47.36187 34.55171 39.34937 44.20013
#> 284 285 286 287 291 292 293 295
#> 50.22983 34.87777 39.67543 44.52619 46.76315 51.47494 36.74710 47.08922
#> 296 298 299 300 301 304 305 306
#> 51.80100 41.26063 46.76315 51.47494 40.19527 55.87340 34.55171 39.34937
#> 307 308 310 311 312 316 317 318
#> 44.20013 50.22983 45.31900 50.16976 56.19946 46.15744 34.55171 39.34937
#> 319 322 323 324 325 327 328 329
#> 44.20013 41.26063 46.76315 51.47494 32.63404 42.97615 47.68794 40.19527
#> 330 331 332 336 339 340 341 342
#> 44.99293 49.84370 55.87340 46.15744 41.44565 46.15744 36.40827 41.20593
#> 343 344 345 347 349 351 352 353
#> 46.05669 52.08639 36.42104 46.76315 32.63404 42.97615 47.68794 32.30798
#> 354 355 356 357 363 364 365 367
#> 37.14756 42.65009 47.36187 30.77748 50.16976 56.19946 40.52133 50.16976
#> 368 370 371 372 373 375 376 378
#> 56.19946 37.14756 42.65009 47.36187 31.10354 41.44565 46.15744 35.94313
#> 379 381 382 384 385 386 388 389
#> 41.44565 32.63404 37.47363 47.68794 40.19527 44.99293 55.87340 30.77748
#> 390 391 392 394 397 398 399 402
#> 35.61706 41.11959 45.83137 37.14756 32.63404 37.47363 42.97615 44.99293
#> 403 405 406 407 408 409 410 411
#> 49.84370 31.10354 35.94313 41.44565 46.15744 31.10354 35.94313 41.44565
#> 413 415 416 418 419 421 422 423
#> 32.63404 42.97615 47.68794 41.20593 46.05669 34.87777 39.67543 44.52619
#> 424 427 428 429 430 431 432 434
#> 50.55589 47.08922 51.80100 40.19527 44.99293 49.84370 55.87340 37.47363
#> 435 436 438 439 444 445 447 449
#> 42.97615 47.68794 39.34937 44.20013 51.80100 32.63404 42.97615 30.77748
#> 450 451 453 454 455 456 457 458
#> 35.61706 41.11959 32.30798 37.14756 42.65009 47.36187 31.10354 35.94313
#> 459 461 463 464 465 469 470 471
#> 41.44565 36.08221 45.73063 51.76033 32.30798 31.10354 35.94313 41.44565
#> 473 474 477 484 487 489 490 491
#> 40.19527 44.99293 31.10354 51.76033 41.44565 36.74710 41.58669 47.08922
#> 494 495 496 497 498 499 501 502
#> 39.67543 44.52619 50.55589 36.42104 41.26063 46.76315 34.55171 39.34937
#> 504 505 508 509 510 511 512 513
#> 50.22983 36.40827 52.08639 34.87777 39.67543 44.52619 50.55589 40.19527
#> 518 519 521 522 523 524 526 527
#> 41.26063 46.76315 31.10354 35.94313 41.44565 46.15744 35.61706 41.11959
#> 528 530 531 532 534 535 536 537
#> 45.83137 41.26063 46.76315 51.47494 37.14756 42.65009 47.36187 32.30798
#> 538 539 540 541 544 545 546 547
#> 37.14756 42.65009 47.36187 40.52133 56.19946 34.87777 39.67543 44.52619
#> 548 549 550 551 555 556 557 558
#> 50.55589 34.55171 39.34937 44.20013 44.52619 50.55589 32.63404 37.47363
#> 560 562 564 569 570 572 573 574
#> 47.68794 44.99293 55.87340 36.40827 41.20593 52.08639 31.10354 35.94313
#> 575 576 577 578 579 582 583 584
#> 41.44565 46.15744 32.30798 37.14756 42.65009 39.67543 44.52619 50.55589
#> 585 586 587 590 591 593 594 595
#> 31.10354 35.94313 41.44565 40.87987 45.73063 31.10354 35.94313 41.44565
#> 596 599 600 601 602 604 606 608
#> 46.15744 46.76315 51.47494 31.10354 35.94313 46.15744 39.67543 50.55589
#> 609 610 611 612 613 614 616 617
#> 32.30798 37.14756 42.65009 47.36187 32.63404 37.47363 47.68794 34.55171
#> 619 620 621 622 623 624 625 628
#> 44.20013 50.22983 36.42104 41.26063 46.76315 51.47494 36.08221 51.76033
#> 630 631 632 633 634 638 639 640
#> 40.87987 45.73063 51.76033 34.87777 39.67543 39.34937 44.20013 50.22983
#> 642 645 648 650 652 654 655 656
#> 37.47363 30.77748 45.83137 41.26063 51.47494 37.47363 42.97615 47.68794
#> 657 661 665 666 668 669 670 671
#> 40.52133 34.55171 32.30798 37.14756 47.36187 32.63404 37.47363 42.97615
#> 673 674 678 679 680 682 684 685
#> 36.74710 41.58669 45.31900 50.16976 56.19946 35.94313 46.15744 34.87777
#> 686 687 689 690 691 693 694 695
#> 39.67543 44.52619 40.52133 45.31900 50.16976 36.40827 41.20593 46.05669
#> 697 698 700 701 702 704 707 709
#> 32.63404 37.47363 47.68794 36.08221 40.87987 51.76033 42.65009 32.30798
#> 712 713 715 716 717 718 719 721
#> 47.36187 40.19527 49.84370 55.87340 30.77748 35.61706 41.11959 31.10354
#> 723 724 727 728 729 730 734 736
#> 41.44565 46.15744 46.05669 52.08639 36.40827 41.20593 45.31900 56.19946
#> 738 739 740 741 742 744 745 749
#> 37.47363 42.97615 47.68794 36.42104 41.26063 51.47494 32.63404 32.63404
#> 751 753 754 755 757 758 759 760
#> 42.97615 34.87777 39.67543 44.52619 36.40827 41.20593 46.05669 52.08639
#> 761 764 765 766 767 768 770 771
#> 40.19527 55.87340 40.52133 45.31900 50.16976 56.19946 35.61706 41.11959
#> 772 773 774 775 776 778 779 781
#> 45.83137 32.30798 37.14756 42.65009 47.36187 45.31900 50.16976 30.77748
#> 782 784 788 789 790 792 797 798
#> 35.61706 45.83137 47.36187 36.08221 40.87987 51.76033 32.30798 37.14756
#> 800
#> 47.36187
# Model frame:
model.frame(object)
#> FEV1 RACE SEX ARMCD AVISIT
#> 2 39.97105 Black or African American Female TRT VIS2
#> 4 20.48379 Black or African American Female TRT VIS4
#> 6 31.45522 Asian Male PBO VIS2
#> 7 36.87889 Asian Male PBO VIS3
#> 8 48.80809 Asian Male PBO VIS4
#> 10 35.98699 Black or African American Female PBO VIS2
#> 12 37.16444 Black or African American Female PBO VIS4
#> 13 33.89229 Asian Female TRT VIS1
#> 14 33.74637 Asian Female TRT VIS2
#> 16 54.45055 Asian Female TRT VIS4
#> 17 32.31386 Black or African American Male PBO VIS1
#> 19 46.79361 Black or African American Male PBO VIS3
#> 20 41.71154 Black or African American Male PBO VIS4
#> 23 39.02423 Black or African American Male PBO VIS3
#> 25 31.93050 Asian Female PBO VIS1
#> 26 32.90947 Asian Female PBO VIS2
#> 28 48.28031 Asian Female PBO VIS4
#> 29 32.23021 Black or African American Male PBO VIS1
#> 30 35.91080 Black or African American Male PBO VIS2
#> 31 45.54898 Black or African American Male PBO VIS3
#> 32 53.02877 Black or African American Male PBO VIS4
#> 33 47.16898 White Male TRT VIS1
#> 34 46.64287 White Male TRT VIS2
#> 36 58.09713 White Male TRT VIS4
#> 39 44.97613 Black or African American Female PBO VIS3
#> 41 44.32755 Asian Female TRT VIS1
#> 42 38.97813 Asian Female TRT VIS2
#> 43 43.72862 Asian Female TRT VIS3
#> 44 46.43393 Asian Female TRT VIS4
#> 45 40.34576 Asian Male PBO VIS1
#> 46 42.76568 Asian Male PBO VIS2
#> 47 40.11155 Asian Male PBO VIS3
#> 51 53.31791 White Male TRT VIS3
#> 52 56.07641 White Male TRT VIS4
#> 55 41.90837 Black or African American Male PBO VIS3
#> 59 34.65663 Asian Male PBO VIS3
#> 60 39.07791 Asian Male PBO VIS4
#> 62 35.89612 Asian Female PBO VIS2
#> 64 47.67264 Asian Female PBO VIS4
#> 65 22.65440 White Female PBO VIS1
#> 68 40.85376 White Female PBO VIS4
#> 69 32.60048 Asian Male TRT VIS1
#> 70 33.64329 Asian Male TRT VIS2
#> 72 40.92278 Asian Male TRT VIS4
#> 73 32.14831 Asian Male TRT VIS1
#> 74 46.43604 Asian Male TRT VIS2
#> 75 41.34973 Asian Male TRT VIS3
#> 76 66.30382 Asian Male TRT VIS4
#> 78 47.95358 White Female TRT VIS2
#> 79 53.97364 White Female TRT VIS3
#> 82 56.64544 White Male TRT VIS2
#> 83 49.70872 White Male TRT VIS3
#> 84 60.40497 White Male TRT VIS4
#> 85 45.98525 White Male TRT VIS1
#> 86 51.90911 White Male TRT VIS2
#> 87 41.50787 White Male TRT VIS3
#> 88 53.42727 White Male TRT VIS4
#> 89 23.86859 Black or African American Female PBO VIS1
#> 90 35.98563 Black or African American Female PBO VIS2
#> 91 43.60626 Black or African American Female PBO VIS3
#> 93 29.59773 White Female TRT VIS1
#> 94 35.50688 White Female TRT VIS2
#> 95 55.42944 White Female TRT VIS3
#> 96 52.10530 White Female TRT VIS4
#> 97 31.69644 White Female TRT VIS1
#> 98 32.16159 White Female TRT VIS2
#> 99 51.04735 White Female TRT VIS3
#> 100 55.85987 White Female TRT VIS4
#> 101 49.11706 White Female TRT VIS1
#> 102 49.25544 White Female TRT VIS2
#> 103 51.72211 White Female TRT VIS3
#> 104 69.99128 White Female TRT VIS4
#> 105 22.07169 Black or African American Female TRT VIS1
#> 107 46.08393 Black or African American Female TRT VIS3
#> 108 52.42288 Black or African American Female TRT VIS4
#> 109 37.69466 Black or African American Male TRT VIS1
#> 110 44.59400 Black or African American Male TRT VIS2
#> 111 52.08897 Black or African American Male TRT VIS3
#> 112 58.22961 Black or African American Male TRT VIS4
#> 113 37.22824 Black or African American Male TRT VIS1
#> 114 34.39863 Black or African American Male TRT VIS2
#> 116 36.34012 Black or African American Male TRT VIS4
#> 117 45.44182 Asian Female TRT VIS1
#> 118 41.54847 Asian Female TRT VIS2
#> 119 43.92172 Asian Female TRT VIS3
#> 120 61.83243 Asian Female TRT VIS4
#> 121 27.25656 Asian Female PBO VIS1
#> 123 45.65133 Asian Female PBO VIS3
#> 125 33.19334 Black or African American Male TRT VIS1
#> 128 41.66826 Black or African American Male TRT VIS4
#> 129 27.12753 Black or African American Male TRT VIS1
#> 130 31.74858 Black or African American Male TRT VIS2
#> 132 41.60000 Black or African American Male TRT VIS4
#> 133 39.45250 Asian Female PBO VIS1
#> 134 32.61823 Asian Female PBO VIS2
#> 135 34.62445 Asian Female PBO VIS3
#> 136 45.90515 Asian Female PBO VIS4
#> 137 36.17780 Black or African American Female TRT VIS1
#> 138 39.79796 Black or African American Female TRT VIS2
#> 140 50.08272 Black or African American Female TRT VIS4
#> 142 44.64316 Asian Female TRT VIS2
#> 144 39.73529 Asian Female TRT VIS4
#> 145 34.06164 White Female PBO VIS1
#> 146 40.18592 White Female PBO VIS2
#> 147 41.17584 White Female PBO VIS3
#> 148 57.76669 White Female PBO VIS4
#> 149 38.18460 Asian Female PBO VIS1
#> 151 47.19893 Asian Female PBO VIS3
#> 153 37.32785 Asian Female PBO VIS1
#> 155 43.16048 Asian Female PBO VIS3
#> 156 41.40349 Asian Female PBO VIS4
#> 157 30.15733 Black or African American Male PBO VIS1
#> 158 35.84353 Black or African American Male PBO VIS2
#> 159 40.95250 Black or African American Male PBO VIS3
#> 162 41.37928 Black or African American Male PBO VIS2
#> 163 50.17316 Black or African American Male PBO VIS3
#> 164 45.35226 Black or African American Male PBO VIS4
#> 165 39.06491 Black or African American Male PBO VIS1
#> 168 42.11960 Black or African American Male PBO VIS4
#> 169 29.81042 Black or African American Female TRT VIS1
#> 170 42.57055 Black or African American Female TRT VIS2
#> 171 47.81652 Black or African American Female TRT VIS3
#> 172 68.06024 Black or African American Female TRT VIS4
#> 173 35.62071 Black or African American Male TRT VIS1
#> 177 33.89134 Asian Female PBO VIS1
#> 178 36.42808 Asian Female PBO VIS2
#> 179 37.57519 Asian Female PBO VIS3
#> 180 58.46873 Asian Female PBO VIS4
#> 181 19.54516 Asian Male PBO VIS1
#> 182 31.13541 Asian Male PBO VIS2
#> 183 40.89955 Asian Male PBO VIS3
#> 185 22.18809 Asian Male TRT VIS1
#> 186 41.05857 Asian Male TRT VIS2
#> 187 37.32452 Asian Male TRT VIS3
#> 190 43.12432 Black or African American Male PBO VIS2
#> 191 41.99349 Black or African American Male PBO VIS3
#> 193 44.03080 White Female PBO VIS1
#> 194 38.66417 White Female PBO VIS2
#> 195 53.45993 White Female PBO VIS3
#> 197 29.81948 Asian Female TRT VIS1
#> 198 30.43859 Asian Female TRT VIS2
#> 199 40.18095 Asian Female TRT VIS3
#> 201 26.78578 Black or African American Female TRT VIS1
#> 202 34.55115 Black or African American Female TRT VIS2
#> 204 40.06421 Black or African American Female TRT VIS4
#> 206 43.09329 Black or African American Female TRT VIS2
#> 208 45.71567 Black or African American Female TRT VIS4
#> 209 40.74992 White Male PBO VIS1
#> 210 44.74635 White Male PBO VIS2
#> 217 40.14674 Asian Male TRT VIS1
#> 218 48.75859 Asian Male TRT VIS2
#> 219 46.43462 Asian Male TRT VIS3
#> 221 29.33990 Black or African American Male PBO VIS1
#> 224 47.93165 Black or African American Male PBO VIS4
#> 226 41.11632 Black or African American Male TRT VIS2
#> 227 47.05889 Black or African American Male TRT VIS3
#> 228 52.24599 Black or African American Male TRT VIS4
#> 230 54.14236 White Female TRT VIS2
#> 231 50.44618 White Female TRT VIS3
#> 233 37.53657 White Female TRT VIS1
#> 235 49.45840 White Female TRT VIS3
#> 236 59.12866 White Female TRT VIS4
#> 237 40.31268 Black or African American Female TRT VIS1
#> 238 39.66049 Black or African American Female TRT VIS2
#> 239 50.89726 Black or African American Female TRT VIS3
#> 240 56.13116 Black or African American Female TRT VIS4
#> 241 32.82981 Asian Male TRT VIS1
#> 242 46.53837 Asian Male TRT VIS2
#> 244 51.81265 Asian Male TRT VIS4
#> 246 29.91939 Asian Female PBO VIS2
#> 250 51.05656 White Female PBO VIS2
#> 251 50.50059 White Female PBO VIS3
#> 252 64.11388 White Female PBO VIS4
#> 253 32.21843 Black or African American Female PBO VIS1
#> 254 29.64732 Black or African American Female PBO VIS2
#> 256 45.09919 Black or African American Female PBO VIS4
#> 257 39.75659 Asian Female TRT VIS1
#> 258 37.28894 Asian Female TRT VIS2
#> 259 44.80145 Asian Female TRT VIS3
#> 260 65.95920 Asian Female TRT VIS4
#> 261 33.43439 Asian Male TRT VIS1
#> 262 33.57042 Asian Male TRT VIS2
#> 263 39.91543 Asian Male TRT VIS3
#> 264 49.57098 Asian Male TRT VIS4
#> 265 38.91634 White Female TRT VIS1
#> 266 36.69011 White Female TRT VIS2
#> 267 45.66665 White Female TRT VIS3
#> 268 52.07431 White Female TRT VIS4
#> 269 42.21411 White Female TRT VIS1
#> 270 45.02901 White Female TRT VIS2
#> 273 30.98338 Black or African American Male PBO VIS1
#> 274 44.72932 Black or African American Male PBO VIS2
#> 275 40.68711 Black or African American Male PBO VIS3
#> 276 34.71530 Black or African American Male PBO VIS4
#> 277 27.30752 Black or African American Male PBO VIS1
#> 278 37.31585 Black or African American Male PBO VIS2
#> 280 44.83000 Black or African American Male PBO VIS4
#> 281 32.93042 Asian Male TRT VIS1
#> 282 44.91911 Asian Male TRT VIS2
#> 283 45.68636 Asian Male TRT VIS3
#> 284 65.98800 Asian Male TRT VIS4
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#> 331 50.69556 White Male TRT VIS3
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model.frame(object, exclude = "subject_var")
#> FEV1 RACE SEX ARMCD AVISIT
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#> 183 40.89955 Asian Male PBO VIS3
#> 185 22.18809 Asian Male TRT VIS1
#> 186 41.05857 Asian Male TRT VIS2
#> 187 37.32452 Asian Male TRT VIS3
#> 190 43.12432 Black or African American Male PBO VIS2
#> 191 41.99349 Black or African American Male PBO VIS3
#> 193 44.03080 White Female PBO VIS1
#> 194 38.66417 White Female PBO VIS2
#> 195 53.45993 White Female PBO VIS3
#> 197 29.81948 Asian Female TRT VIS1
#> 198 30.43859 Asian Female TRT VIS2
#> 199 40.18095 Asian Female TRT VIS3
#> 201 26.78578 Black or African American Female TRT VIS1
#> 202 34.55115 Black or African American Female TRT VIS2
#> 204 40.06421 Black or African American Female TRT VIS4
#> 206 43.09329 Black or African American Female TRT VIS2
#> 208 45.71567 Black or African American Female TRT VIS4
#> 209 40.74992 White Male PBO VIS1
#> 210 44.74635 White Male PBO VIS2
#> 217 40.14674 Asian Male TRT VIS1
#> 218 48.75859 Asian Male TRT VIS2
#> 219 46.43462 Asian Male TRT VIS3
#> 221 29.33990 Black or African American Male PBO VIS1
#> 224 47.93165 Black or African American Male PBO VIS4
#> 226 41.11632 Black or African American Male TRT VIS2
#> 227 47.05889 Black or African American Male TRT VIS3
#> 228 52.24599 Black or African American Male TRT VIS4
#> 230 54.14236 White Female TRT VIS2
#> 231 50.44618 White Female TRT VIS3
#> 233 37.53657 White Female TRT VIS1
#> 235 49.45840 White Female TRT VIS3
#> 236 59.12866 White Female TRT VIS4
#> 237 40.31268 Black or African American Female TRT VIS1
#> 238 39.66049 Black or African American Female TRT VIS2
#> 239 50.89726 Black or African American Female TRT VIS3
#> 240 56.13116 Black or African American Female TRT VIS4
#> 241 32.82981 Asian Male TRT VIS1
#> 242 46.53837 Asian Male TRT VIS2
#> 244 51.81265 Asian Male TRT VIS4
#> 246 29.91939 Asian Female PBO VIS2
#> 250 51.05656 White Female PBO VIS2
#> 251 50.50059 White Female PBO VIS3
#> 252 64.11388 White Female PBO VIS4
#> 253 32.21843 Black or African American Female PBO VIS1
#> 254 29.64732 Black or African American Female PBO VIS2
#> 256 45.09919 Black or African American Female PBO VIS4
#> 257 39.75659 Asian Female TRT VIS1
#> 258 37.28894 Asian Female TRT VIS2
#> 259 44.80145 Asian Female TRT VIS3
#> 260 65.95920 Asian Female TRT VIS4
#> 261 33.43439 Asian Male TRT VIS1
#> 262 33.57042 Asian Male TRT VIS2
#> 263 39.91543 Asian Male TRT VIS3
#> 264 49.57098 Asian Male TRT VIS4
#> 265 38.91634 White Female TRT VIS1
#> 266 36.69011 White Female TRT VIS2
#> 267 45.66665 White Female TRT VIS3
#> 268 52.07431 White Female TRT VIS4
#> 269 42.21411 White Female TRT VIS1
#> 270 45.02901 White Female TRT VIS2
#> 273 30.98338 Black or African American Male PBO VIS1
#> 274 44.72932 Black or African American Male PBO VIS2
#> 275 40.68711 Black or African American Male PBO VIS3
#> 276 34.71530 Black or African American Male PBO VIS4
#> 277 27.30752 Black or African American Male PBO VIS1
#> 278 37.31585 Black or African American Male PBO VIS2
#> 280 44.83000 Black or African American Male PBO VIS4
#> 281 32.93042 Asian Male TRT VIS1
#> 282 44.91911 Asian Male TRT VIS2
#> 283 45.68636 Asian Male TRT VIS3
#> 284 65.98800 Asian Male TRT VIS4
#> 285 46.60130 Asian Female TRT VIS1
#> 286 40.89786 Asian Female TRT VIS2
#> 287 46.66708 Asian Female TRT VIS3
#> 291 43.83270 White Male PBO VIS3
#> 292 44.11604 White Male PBO VIS4
#> 293 38.29612 White Female PBO VIS1
#> 295 51.38570 White Female PBO VIS3
#> 296 56.20979 White Female PBO VIS4
#> 298 43.45819 White Male PBO VIS2
#> 299 38.38741 White Male PBO VIS3
#> 300 56.42818 White Male PBO VIS4
#> 301 39.05050 White Male TRT VIS1
#> 304 54.09200 White Male TRT VIS4
#> 305 31.40521 Asian Male TRT VIS1
#> 306 46.13330 Asian Male TRT VIS2
#> 307 45.29845 Asian Male TRT VIS3
#> 308 28.06936 Asian Male TRT VIS4
#> 310 42.50283 White Female TRT VIS2
#> 311 46.45368 White Female TRT VIS3
#> 312 64.97366 White Female TRT VIS4
#> 316 43.97847 Asian Female PBO VIS4
#> 317 35.33466 Asian Male TRT VIS1
#> 318 39.34378 Asian Male TRT VIS2
#> 319 41.27633 Asian Male TRT VIS3
#> 322 39.83058 White Male PBO VIS2
#> 323 43.49673 White Male PBO VIS3
#> 324 44.06114 White Male PBO VIS4
#> 325 41.43742 Black or African American Female PBO VIS1
#> 327 46.16954 Black or African American Female PBO VIS3
#> 328 54.24024 Black or African American Female PBO VIS4
#> 329 36.61831 White Male TRT VIS1
#> 330 42.09272 White Male TRT VIS2
#> 331 50.69556 White Male TRT VIS3
#> 332 51.72563 White Male TRT VIS4
#> 336 53.89947 Asian Female PBO VIS4
#> 339 39.94420 Asian Female PBO VIS3
#> 340 56.42482 Asian Female PBO VIS4
#> 341 41.86385 Black or African American Female TRT VIS1
#> 342 34.56420 Black or African American Female TRT VIS2
#> 343 38.68927 Black or African American Female TRT VIS3
#> 344 62.88743 Black or African American Female TRT VIS4
#> 345 28.85343 White Male PBO VIS1
#> 347 49.29495 White Male PBO VIS3
#> 349 28.74029 Black or African American Female PBO VIS1
#> 351 43.59994 Black or African American Female PBO VIS3
#> 352 57.38616 Black or African American Female PBO VIS4
#> 353 35.36824 Black or African American Male PBO VIS1
#> 354 43.06110 Black or African American Male PBO VIS2
#> 355 31.27551 Black or African American Male PBO VIS3
#> 356 54.13245 Black or African American Male PBO VIS4
#> 357 25.97050 Asian Male PBO VIS1
#> 363 51.17493 White Female TRT VIS3
#> 364 48.44043 White Female TRT VIS4
#> 365 43.33128 White Female TRT VIS1
#> 367 55.93546 White Female TRT VIS3
#> 368 54.15312 White Female TRT VIS4
#> 370 40.60252 Black or African American Male PBO VIS2
#> 371 44.44715 Black or African American Male PBO VIS3
#> 372 40.54161 Black or African American Male PBO VIS4
#> 373 33.95563 Asian Female PBO VIS1
#> 375 43.67802 Asian Female PBO VIS3
#> 376 42.76023 Asian Female PBO VIS4
#> 378 42.82678 Asian Female PBO VIS2
#> 379 39.59218 Asian Female PBO VIS3
#> 381 33.49216 Black or African American Female PBO VIS1
#> 382 35.39266 Black or African American Female PBO VIS2
#> 384 42.36266 Black or African American Female PBO VIS4
#> 385 48.54368 White Male TRT VIS1
#> 386 43.94366 White Male TRT VIS2
#> 388 47.91204 White Male TRT VIS4
#> 389 20.72928 Asian Male PBO VIS1
#> 390 28.00599 Asian Male PBO VIS2
#> 391 40.19255 Asian Male PBO VIS3
#> 392 37.79360 Asian Male PBO VIS4
#> 394 36.75177 Black or African American Male PBO VIS2
#> 397 34.59822 Black or African American Female PBO VIS1
#> 398 39.32034 Black or African American Female PBO VIS2
#> 399 40.65702 Black or African American Female PBO VIS3
#> 402 43.03255 White Male TRT VIS2
#> 403 54.65715 White Male TRT VIS3
#> 405 35.55742 Asian Female PBO VIS1
#> 406 43.70215 Asian Female PBO VIS2
#> 407 42.52157 Asian Female PBO VIS3
#> 408 54.89337 Asian Female PBO VIS4
#> 409 32.03460 Asian Female PBO VIS1
#> 410 29.45107 Asian Female PBO VIS2
#> 411 45.35138 Asian Female PBO VIS3
#> 413 38.73784 Black or African American Female PBO VIS1
#> 415 41.42283 Black or African American Female PBO VIS3
#> 416 47.32385 Black or African American Female PBO VIS4
#> 418 47.55310 Black or African American Female TRT VIS2
#> 419 49.06509 Black or African American Female TRT VIS3
#> 421 29.22591 Asian Female TRT VIS1
#> 422 40.08175 Asian Female TRT VIS2
#> 423 45.68142 Asian Female TRT VIS3
#> 424 41.47403 Asian Female TRT VIS4
#> 427 42.51970 White Female PBO VIS3
#> 428 69.36099 White Female PBO VIS4
#> 429 42.39760 White Male TRT VIS1
#> 430 43.72376 White Male TRT VIS2
#> 431 49.47601 White Male TRT VIS3
#> 432 51.94188 White Male TRT VIS4
#> 434 40.59100 Black or African American Female PBO VIS2
#> 435 39.97833 Black or African American Female PBO VIS3
#> 436 31.69049 Black or African American Female PBO VIS4
#> 438 37.20517 Asian Male TRT VIS2
#> 439 46.28740 Asian Male TRT VIS3
#> 444 41.58720 White Female PBO VIS4
#> 445 32.17365 Black or African American Female PBO VIS1
#> 447 40.69375 Black or African American Female PBO VIS3
#> 449 32.28771 Asian Male PBO VIS1
#> 450 41.76205 Asian Male PBO VIS2
#> 451 40.06768 Asian Male PBO VIS3
#> 453 29.14213 Black or African American Male PBO VIS1
#> 454 39.50989 Black or African American Male PBO VIS2
#> 455 43.32349 Black or African American Male PBO VIS3
#> 456 47.16756 Black or African American Male PBO VIS4
#> 457 40.93020 Asian Female PBO VIS1
#> 458 42.19406 Asian Female PBO VIS2
#> 459 41.21057 Asian Female PBO VIS3
#> 461 38.54330 Black or African American Male TRT VIS1
#> 463 43.96324 Black or African American Male TRT VIS3
#> 464 42.67652 Black or African American Male TRT VIS4
#> 465 22.79584 Black or African American Male PBO VIS1
#> 469 31.43559 Asian Female PBO VIS1
#> 470 38.85064 Asian Female PBO VIS2
#> 471 48.24288 Asian Female PBO VIS3
#> 473 44.71302 White Male TRT VIS1
#> 474 51.85370 White Male TRT VIS2
#> 477 30.56757 Asian Female PBO VIS1
#> 484 59.90473 Black or African American Male TRT VIS4
#> 487 49.76150 Asian Female PBO VIS3
#> 489 47.21985 White Female PBO VIS1
#> 490 40.34525 White Female PBO VIS2
#> 491 48.29793 White Female PBO VIS3
#> 494 44.39634 Asian Female TRT VIS2
#> 495 41.71421 Asian Female TRT VIS3
#> 496 47.37535 Asian Female TRT VIS4
#> 497 42.03797 White Male PBO VIS1
#> 498 37.56100 White Male PBO VIS2
#> 499 45.11793 White Male PBO VIS3
#> 501 34.62530 Asian Male TRT VIS1
#> 502 45.28206 Asian Male TRT VIS2
#> 504 63.57761 Asian Male TRT VIS4
#> 505 35.80878 Black or African American Female TRT VIS1
#> 508 52.67314 Black or African American Female TRT VIS4
#> 509 35.88734 Asian Female TRT VIS1
#> 510 38.73222 Asian Female TRT VIS2
#> 511 46.70361 Asian Female TRT VIS3
#> 512 53.65398 Asian Female TRT VIS4
#> 513 36.71543 White Male TRT VIS1
#> 518 41.54317 White Male PBO VIS2
#> 519 51.67909 White Male PBO VIS3
#> 521 27.40130 Asian Female PBO VIS1
#> 522 30.33517 Asian Female PBO VIS2
#> 523 37.73092 Asian Female PBO VIS3
#> 524 29.11668 Asian Female PBO VIS4
#> 526 32.08830 Asian Male PBO VIS2
#> 527 41.66067 Asian Male PBO VIS3
#> 528 53.90815 Asian Male PBO VIS4
#> 530 35.06937 White Male PBO VIS2
#> 531 47.17615 White Male PBO VIS3
#> 532 56.49347 White Male PBO VIS4
#> 534 38.88006 Black or African American Male PBO VIS2
#> 535 47.54070 Black or African American Male PBO VIS3
#> 536 43.53705 Black or African American Male PBO VIS4
#> 537 31.82054 Black or African American Male PBO VIS1
#> 538 39.62816 Black or African American Male PBO VIS2
#> 539 44.95543 Black or African American Male PBO VIS3
#> 540 21.11543 Black or African American Male PBO VIS4
#> 541 34.74671 White Female TRT VIS1
#> 544 56.69249 White Female TRT VIS4
#> 545 22.73126 Asian Female TRT VIS1
#> 546 32.50075 Asian Female TRT VIS2
#> 547 42.37206 Asian Female TRT VIS3
#> 548 42.89847 Asian Female TRT VIS4
#> 549 55.62582 Asian Male TRT VIS1
#> 550 45.38998 Asian Male TRT VIS2
#> 551 52.66743 Asian Male TRT VIS3
#> 555 34.18931 Asian Female TRT VIS3
#> 556 45.59740 Asian Female TRT VIS4
#> 557 28.89198 Black or African American Female PBO VIS1
#> 558 38.46147 Black or African American Female PBO VIS2
#> 560 49.90357 Black or African American Female PBO VIS4
#> 562 44.14167 White Male TRT VIS2
#> 564 55.24278 White Male TRT VIS4
#> 569 27.38001 Black or African American Female TRT VIS1
#> 570 33.63251 Black or African American Female TRT VIS2
#> 572 39.34410 Black or African American Female TRT VIS4
#> 573 26.98575 Asian Female PBO VIS1
#> 574 24.04175 Asian Female PBO VIS2
#> 575 42.16648 Asian Female PBO VIS3
#> 576 44.75380 Asian Female PBO VIS4
#> 577 31.55469 Black or African American Male PBO VIS1
#> 578 44.42696 Black or African American Male PBO VIS2
#> 579 44.10343 Black or African American Male PBO VIS3
#> 582 37.87445 Asian Female TRT VIS2
#> 583 48.31828 Asian Female TRT VIS3
#> 584 50.21520 Asian Female TRT VIS4
#> 585 41.94615 Asian Female PBO VIS1
#> 586 39.62690 Asian Female PBO VIS2
#> 587 46.69763 Asian Female PBO VIS3
#> 590 43.75255 Black or African American Male TRT VIS2
#> 591 47.38873 Black or African American Male TRT VIS3
#> 593 32.43412 Asian Female PBO VIS1
#> 594 43.07163 Asian Female PBO VIS2
#> 595 42.99551 Asian Female PBO VIS3
#> 596 53.82759 Asian Female PBO VIS4
#> 599 50.64802 White Male PBO VIS3
#> 600 63.44051 White Male PBO VIS4
#> 601 34.48949 Asian Female PBO VIS1
#> 602 40.08056 Asian Female PBO VIS2
#> 604 47.46553 Asian Female PBO VIS4
#> 606 37.11697 Asian Female TRT VIS2
#> 608 36.25120 Asian Female TRT VIS4
#> 609 29.20171 Black or African American Male PBO VIS1
#> 610 31.53773 Black or African American Male PBO VIS2
#> 611 42.35683 Black or African American Male PBO VIS3
#> 612 64.78352 Black or African American Male PBO VIS4
#> 613 32.72757 Black or African American Female PBO VIS1
#> 614 37.50022 Black or African American Female PBO VIS2
#> 616 57.03861 Black or African American Female PBO VIS4
#> 617 36.32475 Asian Male TRT VIS1
#> 619 41.46725 Asian Male TRT VIS3
#> 620 59.01411 Asian Male TRT VIS4
#> 621 30.14970 White Male PBO VIS1
#> 622 34.91740 White Male PBO VIS2
#> 623 52.13900 White Male PBO VIS3
#> 624 58.73839 White Male PBO VIS4
#> 625 35.83185 Black or African American Male TRT VIS1
#> 628 56.41409 Black or African American Male TRT VIS4
#> 630 43.55593 Black or African American Male TRT VIS2
#> 631 44.26320 Black or African American Male TRT VIS3
#> 632 59.25579 Black or African American Male TRT VIS4
#> 633 28.47314 Asian Female TRT VIS1
#> 634 47.47581 Asian Female TRT VIS2
#> 638 46.47483 Asian Male TRT VIS2
#> 639 51.22677 Asian Male TRT VIS3
#> 640 45.82777 Asian Male TRT VIS4
#> 642 39.06783 Black or African American Female PBO VIS2
#> 645 29.99542 Asian Male PBO VIS1
#> 648 54.17796 Asian Male PBO VIS4
#> 650 44.55743 White Male PBO VIS2
#> 652 62.59579 White Male PBO VIS4
#> 654 35.48396 Black or African American Female PBO VIS2
#> 655 44.07768 Black or African American Female PBO VIS3
#> 656 46.57837 Black or African American Female PBO VIS4
#> 657 47.67979 White Female TRT VIS1
#> 661 22.15439 Asian Male TRT VIS1
#> 665 34.27765 Black or African American Male PBO VIS1
#> 666 36.90059 Black or African American Male PBO VIS2
#> 668 40.54285 Black or African American Male PBO VIS4
#> 669 29.09494 Black or African American Female PBO VIS1
#> 670 37.21768 Black or African American Female PBO VIS2
#> 671 43.08491 Black or African American Female PBO VIS3
#> 673 27.12174 White Female PBO VIS1
#> 674 34.11916 White Female PBO VIS2
#> 678 40.80230 White Female TRT VIS2
#> 679 45.89269 White Female TRT VIS3
#> 680 43.69153 White Female TRT VIS4
#> 682 29.22869 Asian Female PBO VIS2
#> 684 55.68362 Asian Female PBO VIS4
#> 685 31.90698 Asian Female TRT VIS1
#> 686 37.31061 Asian Female TRT VIS2
#> 687 40.75546 Asian Female TRT VIS3
#> 689 42.19474 White Female TRT VIS1
#> 690 44.87228 White Female TRT VIS2
#> 691 47.55198 White Female TRT VIS3
#> 693 50.62894 Black or African American Female TRT VIS1
#> 694 45.47551 Black or African American Female TRT VIS2
#> 695 48.62168 Black or African American Female TRT VIS3
#> 697 29.66493 Black or African American Female PBO VIS1
#> 698 34.57406 Black or African American Female PBO VIS2
#> 700 38.11676 Black or African American Female PBO VIS4
#> 701 33.77204 Black or African American Male TRT VIS1
#> 702 34.26148 Black or African American Male TRT VIS2
#> 704 58.81037 Black or African American Male TRT VIS4
#> 707 39.88119 Black or African American Male PBO VIS3
#> 709 31.62708 Black or African American Male PBO VIS1
#> 712 48.22049 Black or African American Male PBO VIS4
#> 713 42.58829 White Male TRT VIS1
#> 715 49.33262 White Male TRT VIS3
#> 716 53.74331 White Male TRT VIS4
#> 717 29.71857 Asian Male PBO VIS1
#> 718 30.45651 Asian Male PBO VIS2
#> 719 38.29800 Asian Male PBO VIS3
#> 721 36.81040 Asian Female PBO VIS1
#> 723 42.35045 Asian Female PBO VIS3
#> 724 39.39860 Asian Female PBO VIS4
#> 727 49.73629 Black or African American Female TRT VIS3
#> 728 41.58082 Black or African American Female TRT VIS4
#> 729 43.58901 Black or African American Female TRT VIS1
#> 730 40.16762 Black or African American Female TRT VIS2
#> 734 41.08206 White Female TRT VIS2
#> 736 69.37409 White Female TRT VIS4
#> 738 41.27625 Black or African American Female PBO VIS2
#> 739 44.76138 Black or African American Female PBO VIS3
#> 740 39.69815 Black or African American Female PBO VIS4
#> 741 38.44296 White Male PBO VIS1
#> 742 48.20586 White Male PBO VIS2
#> 744 35.50735 White Male PBO VIS4
#> 745 32.08153 Black or African American Female PBO VIS1
#> 749 44.69256 Black or African American Female PBO VIS1
#> 751 42.18689 Black or African American Female PBO VIS3
#> 753 37.01741 Asian Female TRT VIS1
#> 754 38.26920 Asian Female TRT VIS2
#> 755 49.28806 Asian Female TRT VIS3
#> 757 40.45953 Black or African American Female TRT VIS1
#> 758 45.10337 Black or African American Female TRT VIS2
#> 759 45.58250 Black or African American Female TRT VIS3
#> 760 62.96989 Black or African American Female TRT VIS4
#> 761 30.78252 White Male TRT VIS1
#> 764 44.69667 White Male TRT VIS4
#> 765 32.72491 White Female TRT VIS1
#> 766 45.78702 White Female TRT VIS2
#> 767 48.74886 White Female TRT VIS3
#> 768 84.08449 White Female TRT VIS4
#> 770 30.19495 Asian Male PBO VIS2
#> 771 36.78573 Asian Male PBO VIS3
#> 772 61.03588 Asian Male PBO VIS4
#> 773 20.36749 Black or African American Male PBO VIS1
#> 774 35.22480 Black or African American Male PBO VIS2
#> 775 37.42847 Black or African American Male PBO VIS3
#> 776 30.20501 Black or African American Male PBO VIS4
#> 778 49.12862 White Female TRT VIS2
#> 779 47.31234 White Female TRT VIS3
#> 781 19.28388 Asian Male PBO VIS1
#> 782 30.00682 Asian Male PBO VIS2
#> 784 49.21768 Asian Male PBO VIS4
#> 788 40.13353 Black or African American Male PBO VIS4
#> 789 42.34534 Black or African American Male TRT VIS1
#> 790 52.32575 Black or African American Male TRT VIS2
#> 792 69.26254 Black or African American Male TRT VIS4
#> 797 35.70341 Black or African American Male PBO VIS1
#> 798 41.64454 Black or African American Male PBO VIS2
#> 800 54.25081 Black or African American Male PBO VIS4
# Log likelihood given the estimated parameters:
logLik(object)
#> [1] -1693.225
# Formula which was used:
formula(object)
#> FEV1 ~ RACE + SEX + ARMCD * AVISIT + us(AVISIT | USUBJID)
#> <environment: 0x55c9beed86a0>
# Variance-covariance matrix estimate for coefficients:
vcov(object)
#> (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
# Variance-covariance matrix estimate for residuals:
VarCorr(object)
#> 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
# REML criterion (twice the negative log likelihood):
deviance(object)
#> [1] 3386.45
# AIC:
AIC(object)
#> [1] 3406.45
AIC(object, corrected = TRUE)
#> [1] 3406.877
# BIC:
BIC(object)
#> [1] 3439.282
# residuals:
residuals(object, type = "response")
#> [1] -1.234879652 -31.602602517 -4.161845076 -4.240694906 2.976720902
#> [6] -1.486633993 -10.523496721 -0.985476011 -5.929054895 3.894654785
#> [11] 0.005884300 4.143525922 -5.650335904 -3.625861923 0.826964231
#> [16] -3.033654140 2.122875942 -0.077764040 -1.236764407 2.898887820
#> [21] 5.666894712 6.973709346 1.649933932 2.223736062 1.999981925
#> [26] 9.449780374 -0.697302530 -0.797571139 -4.121957765 9.568283755
#> [31] 7.148615054 -1.008039398 3.474215960 0.203016560 -0.741716375
#> [36] -6.462963308 -6.753458982 -0.047005589 1.515200267 -14.092698990
#> [41] -10.947245143 -1.951225988 -5.706079812 -9.307052363 -2.403398748
#> [46] 7.086671267 -2.850398916 16.073985815 2.634589860 3.803878882
#> [51] 11.652502799 -0.134982175 4.531571586 5.789979573 6.916172244
#> [56] -8.335823810 -2.446122835 -8.765445294 -1.487993507 0.630113879
#> [61] -10.923600038 -9.812114797 5.259684070 -4.094159929 -8.824895907
#> [66] -13.157401791 0.877589312 -0.339592573 8.595725270 3.936442210
#> [71] 1.552353395 13.791819037 -14.336580048 0.027233096 0.336487818
#> [76] 1.612454504 3.714131743 6.358341554 6.469275659 1.146036288
#> [81] -6.481239981 -15.420209264 10.564048465 1.873040490 -0.604472161
#> [86] 11.276535944 -3.846981011 4.205682602 -2.888867642 -10.092066250
#> [91] -8.954675960 -9.131288225 -10.160328309 8.348966008 -3.324891902
#> [96] -6.821197849 -0.252287406 -0.230464002 -1.407973607 -2.003675274
#> [101] 4.967728097 -10.820604863 -2.685460226 -1.400767701 -5.913374081
#> [106] 5.965692909 7.081065238 5.753275316 6.224314102 1.714833437
#> [111] -4.753946846 -2.150649979 -1.304036547 -1.697593065 4.231714405
#> [116] 7.523067828 -2.009615920 6.756933384 -5.242275398 -6.597847500
#> [121] 1.364617396 1.759820544 15.973845801 -0.461493245 2.787801686
#> [126] 0.484952966 -3.870461666 12.311298679 -11.232317044 -4.481649361
#> [131] -0.220037106 -12.363619506 1.709197627 -6.875616999 5.976752937
#> [136] -0.656597193 7.283701781 -2.922519989 6.370716054 -5.058284328
#> [141] -9.236842335 -4.345245889 -9.622488058 -6.654774813 -12.022180587
#> [146] 1.887357480 -6.370718385 4.328882117 3.485715939 5.595034537
#> [151] 9.409222502 2.234484592 -2.968076876 0.569772634 0.236447831
#> [156] 1.328254786 0.485660327 8.823363223 0.276419270 -2.984758150
#> [161] -0.711357559 2.929205179 3.904409284 -1.545435261 4.840564762
#> [166] 4.044772166 -1.721893559 7.189004781 1.582814876 -6.023735519
#> [171] 9.469873359 3.411370689 12.312877955 -0.415604291 -7.826304065
#> [176] -2.588748144 4.878824125 -2.386492192 0.275251132 15.403304358
#> [181] -1.117311743 -5.778945571 -4.284700514 -0.658853762 -1.604989482
#> [186] -8.628885781 -4.503110575 -4.125143859 1.692779577 -0.289986567
#> [191] -1.324600198 7.581755477 -1.962979124 -12.646575009 -5.000450448
#> [196] 0.168281529 -2.531874945 -1.621285472 5.569746459 1.486223742
#> [201] 15.758167838 11.723532098 1.222430146 2.140888226 -2.930455637
#> [206] -7.358901274 1.549014295 4.296486376 4.408791522 2.197562650
#> [211] -8.375741822 4.953239770 -1.144775488 -1.781395739 -3.146498706
#> [216] 6.783928757 1.098312860 -22.160474609 -2.816167884 -3.716081684
#> [221] 8.774205403 -2.178968843 0.782958690 -0.005585283 -2.923802312
#> [226] -1.430045436 -3.266421082 -7.413799193 8.803384810 3.193392733
#> [231] 6.552308299 -3.576957870 -2.900210364 0.851863016 -4.147762312
#> [236] 7.742038570 -1.501447881 10.267382270 5.455583260 -6.641733868
#> [241] -7.367427023 10.801038359 -7.567612905 2.531801030 -3.893743195
#> [246] 0.623788663 9.698229358 3.060268037 5.913536244 -11.374576033
#> [251] 6.770578888 -4.806976192 1.005172447 -7.759025307 2.809952061
#> [256] 5.765703310 -2.046337220 3.454956181 1.797059893 -6.820263102
#> [261] 2.852094314 2.232372715 -3.397204643 6.883657677 -1.853470422
#> [266] 0.858119403 -2.080961909 -5.325272886 8.348411771 -1.049269637
#> [271] -7.961356400 -10.048198957 -7.611069668 -0.927034289 -8.037769563
#> [276] -0.395791510 1.964185716 1.846717422 -2.319131312 -1.960386265
#> [281] 4.813456009 4.453877656 7.759026726 1.075918408 8.735930253
#> [286] 0.931062886 -6.492053277 3.905731110 6.103802886 -1.553315409
#> [291] -0.364087540 6.347166038 3.008394981 -5.651857454 0.406319494
#> [296] 1.155221279 -9.081862494 -4.569513438 17.559986122 2.202330352
#> [301] -1.269170427 -0.367685386 -3.931511724 3.117376232 -2.997817660
#> [306] -15.997444012 -2.144194495 2.087262596 -10.213796246 -0.460389924
#> [311] -2.282396185 1.510231160 6.144987953 -1.051913357 -3.165847388
#> [316] 2.362323843 0.673403098 -0.194314949 9.826663341 6.250933707
#> [321] -0.235076130 2.461097100 -1.767393574 -9.083814120 -9.512139613
#> [326] 0.332052131 2.907510403 6.797230637 4.517753563 6.860770097
#> [331] -0.535968343 8.144395143 8.315853379 10.472748395 -1.241441160
#> [336] 1.208712197 4.720909904 -2.811983812 -3.180543134 5.616929260
#> [341] -3.699626586 -1.645226149 0.073590117 5.932694905 13.347774651
#> [346] -0.599486961 0.586742528 1.009572681 -0.943207940 2.177417986
#> [351] 3.098085788 -3.479836872 0.282540942 4.915937135 -3.702232983
#> [356] -5.607957192 -3.714729352 -17.040753161 -3.528768581 0.541082039
#> [361] 8.076779586 -6.191258080 0.412993243 5.018532666 1.732496518
#> [366] 4.890613044 -3.824823997 -0.487435234 2.480592663 2.305343529
#> [371] -26.246442718 -5.774618924 0.493027338 -12.146505999 -7.174675073
#> [376] -2.154139764 -7.657419221 21.074111704 6.040615383 8.467296562
#> [381] -10.336888517 -4.958491116 -3.742055183 0.987848599 2.215631522
#> [386] -0.851264659 -0.630616202 -9.028257544 -7.573424167 -12.742297395
#> [391] -4.117784562 -11.901375893 0.720831832 -1.403633842 -0.753280271
#> [396] 7.279393940 1.453345956 -1.800975371 3.792088067 -0.340693264
#> [401] 10.842614257 3.683774850 5.251983786 2.872680103 1.658098849
#> [406] 1.330582219 7.128499486 1.549862924 7.670151870 3.884868504
#> [411] 11.965570612 3.385952871 4.137436188 1.308094515 -2.558461227
#> [416] -14.304693302 -3.106269989 -5.609838571 -0.293261124 17.421651070
#> [421] 0.093535126 0.026595297 9.350679413 1.773045693 -2.732879905
#> [426] 8.784278133 -6.271337496 -6.343229393 5.375845601 7.263453790
#> [431] -0.250360213 4.653760313 2.676065485 -1.467432090 7.495460612
#> [436] -6.404623267 7.800378199 7.125463247 7.026637291 -4.402064897
#> [441] 1.594201571 -0.782053228 8.346582123 3.296803523 11.120854597
#> [446] -1.989665587 1.101524949 -1.109564945 7.158458483 -12.397318171
#> [451] 1.969677544 -0.246975211 -6.819019339 -3.539097324 -0.255945131
#> [456] 0.108762339 -9.625363156 -7.467529543 -4.516696858 -4.277072142
#> [461] -12.507932515 -6.714436823 9.526182803 -2.970783609 -2.364822030
#> [466] -3.770735866 1.673403803 -0.446717846 -2.617775570 14.220675868
#> [471] 4.269581680 2.564985116 -2.969110991 -2.899565420 -9.571178045
#> [476] -2.310163663 -6.618388134 7.050040894 -2.768894832 -0.680898398
#> [481] 0.858618471 2.393017430 -0.511076204 -2.130084682 -1.058901346
#> [486] -5.160549124 -2.821587861 5.706858994 0.904798206 -6.758830844
#> [491] 3.679593184 -10.505575302 7.180743205 -1.038313940 -4.236938656
#> [496] 13.174628062 3.802619676 1.785232749 -7.989780520 2.021917955
#> [501] 6.945228489 -15.967590464 -0.552509306 12.058523414 -0.789256094
#> [506] 2.139638364 -1.406232324 4.761861929 4.051265895 3.897435776
#> [511] -0.474197410 10.883502127 -9.412746363 -11.176728898 -7.796425447
#> [516] 0.468028997 -1.420902629 27.885028986 -5.422118623 -4.333853988
#> [521] 15.204501679 -11.940481268 -1.922768210 -5.221617225 -17.156866508
#> [526] 3.809621210 -2.857420361 -11.493590753 -5.610248116 3.386308297
#> [531] -7.228339769 6.263138946 11.445882539 17.502205607 3.395436537
#> [536] 4.496978998 6.888939057
residuals(object, type = "pearson")
#> [1] -0.2395613408 -3.2328976424 -0.8073800434 -1.0986900855 0.3045139709
#> [6] -0.2884006003 -1.0765375327 -0.1547501250 -1.1502111470 0.3984171957
#> [11] 0.0009240166 1.0735152964 -0.5780206744 -0.9393975831 0.1298588873
#> [16] -0.5885158546 0.2171669446 -0.0122113525 -0.2399269752 0.7510512728
#> [21] 0.5797146151 1.0950874316 0.3200800859 0.2274847797 0.5181604338
#> [26] 1.4839069433 -0.1352736914 -0.2066367711 -0.4216699411 1.5025156286
#> [31] 1.3868005721 -0.2611654261 0.9001087591 0.0207682819 -0.1921657760
#> [36] -1.6744410682 -0.6908684691 -0.0091188820 0.1550026574 -2.2129883504
#> [41] -1.1198863446 -0.3064026546 -1.1069549401 -0.9520971453 -0.3774077226
#> [46] 1.3747837439 -0.7384886436 1.6443440320 0.5110991006 0.9855186723
#> [51] 2.2605354222 -0.0349715273 0.4635728051 0.9092053518 1.3417076669
#> [56] -2.1596665585 -0.2502346046 -1.3764452313 -0.2886643401 0.1632515159
#> [61] -1.7153420821 -1.9035080658 1.3626924050 -0.4188262652 -1.3857808111
#> [66] -2.5524793535 0.2273680841 -0.0347397980 1.3497939535 0.7636528569
#> [71] 0.4021876891 1.4108818799 -2.2512851976 0.0070556201 0.0344221864
#> [76] 0.2532050841 0.7205255825 1.6473353965 0.6617969521 0.1799630402
#> [81] -1.2573326786 -1.5774636961 1.6588813968 0.3633617985 -0.1566081939
#> [86] 1.1535722873 -0.6040946569 1.0896190080 -0.4536413104 -1.0324028588
#> [91] -1.4061602817 -1.7714306394 -1.0393859625 1.3110451395 -0.6450147276
#> [96] -1.7672533895 -0.0258086137 -0.0361899557 -0.2731408237 -0.2049728995
#> [101] 0.9637178832 -1.1069312387 -0.4217000731 -0.2717429089 -1.5320520854
#> [106] 0.6102812112 1.1119456174 1.4905732876 0.9774092675 0.4442834340
#> [111] -0.4863214523 -0.3377183713 -0.2529774810 -0.4398167544 0.8209343927
#> [116] 1.9490956593 -0.2055806185 1.0610469204 -0.5362767122 -1.0360655304
#> [121] 0.2647299052 0.4559388087 1.6340998625 -0.0724686715 0.4377708385
#> [126] 0.0940787894 -1.0027691104 1.2594269238 -1.7638201727 -0.8694206991
#> [131] -0.0570077764 -1.9414695478 0.3315769879 -1.7813524423 1.1594643621
#> [136] -0.1701128805 1.1437658039 -0.5669563073 1.6505414137 -0.7943066334
#> [141] -1.7919076827 -1.1257774216 -1.5110273758 -1.2909976896 -1.2298505876
#> [146] 0.3661392331 -0.6517146946 0.6797679920 0.6762138991 0.8785929692
#> [151] 1.8253486935 0.5789159848 -0.4660796030 0.0582868643 0.0458698622
#> [156] 0.3441276480 0.0496823046 1.7116945134 0.0716154116 -0.4686990773
#> [161] -0.1843003363 0.2996531856 0.6131126668 -0.2998077932 1.2541059023
#> [166] 0.4137739729 -0.2703903907 1.3946360054 0.1619195279 -1.1685787807
#> [171] 1.8371146990 0.8838266455 1.2595884814 -0.0652626906 -1.5182693254
#> [176] -0.2648249544 0.7661258472 -0.4629692202 0.0713127674 1.5757343502
#> [181] -0.1754524008 -1.1210905839 -1.1100911709 -0.0673997268 -0.2520328454
#> [186] -1.6739667261 -1.1666774083 -0.4219958735 0.2658185978 -0.0562561468
#> [191] -0.2080030808 1.4708279512 -0.5085736534 -1.2937251768 -0.7852249307
#> [196] 0.0326458929 -0.2590069136 -0.2545918184 1.0805068560 0.3850546492
#> [201] 1.6120363386 1.8409560848 0.2371461903 0.5546667988 -0.7592299434
#> [206] -0.7528042846 0.2432430148 1.1131446822 0.4510125934 0.4263177017
#> [211] -2.1700086192 0.5067088119 -0.1797650557 -0.1822340449 -0.4940973327
#> [216] 1.3160529992 0.2845537057 -2.2669824765 -0.5463244563 -0.9627719496
#> [221] 0.8975877207 -0.2229051620 0.1229486602 -0.0010835209 -0.7575061831
#> [226] -0.2774226634 -0.8462727304 -0.7584202573 1.3824029054 0.8273523589
#> [231] 0.6702910636 -0.5616926964 -0.5626283359 0.2207028495 -0.4243097065
#> [236] 0.7919986408 -0.3889989582 1.0503374182 0.8566948182 -1.2884678024
#> [241] -1.9087718415 1.1049296155 -1.1883486059 0.6559454881 -0.6114377619
#> [246] 0.1616127626 0.9921139504 0.4805564584 1.1472005954 -2.9469542586
#> [251] 0.6926198092 -0.7548435060 0.2604226491 -0.7937363579 0.4412491305
#> [256] 1.4937931640 -0.2093371509 0.6702466383 0.4655868747 -0.6977024279
#> [261] 0.4478667638 0.5783688342 -0.3475288111 1.3353999808 -0.4802018588
#> [266] 0.1347512101 -0.4036976594 -0.5447672276 1.3109581072 -0.2035537964
#> [271] -0.8144345176 -1.5778771157 -1.4765147781 -0.2401784153 -0.8222514667
#> [276] -0.0767818506 0.3084377315 0.3582552366 -0.6008464735 -0.3803065033
#> [281] 1.2470824973 0.6993961465 1.5052178110 0.2787516936 0.8936722317
#> [286] 0.1462055864 -1.2594304114 1.0119068082 0.9584852901 -0.4024369301
#> [291] -0.0372455955 1.2313229104 0.7794226682 -0.8875159196 0.0788242342
#> [296] 0.2992976843 -0.9290605680 -1.1838812319 1.7963595784 0.3458337835
#> [301] -0.2462136037 -0.0952608705 -0.4021876039 0.6047575802 -0.7766822687
#> [306] -1.6365139232 -0.4159645093 0.5407733334 -1.0448556503 -0.0722954162
#> [311] -0.5913290428 0.2371528666 1.1921012315 -0.2725324036 -0.4971356724
#> [316] 0.4582806645 0.1744669975 -0.0198781205 1.5430891919 1.2126542520
#> [321] -0.0609041252 0.3864681432 -0.4579008486 -0.9292602164 -1.4936992670
#> [326] 0.0521424248 0.5640445122 1.7610439030 0.7094266338 1.3309598886
#> [331] -0.0841635588 0.8331590995 2.1544925682 1.6445444703 -0.2408342453
#> [336] 0.3131562482 0.9158362154 -0.7285359600 -0.3253646719 0.8820311160
#> [341] -0.7177116444 -0.4262493998 0.0115559178 1.1509172932 1.3654568220
#> [346] -0.0941379407 0.0600228584 0.1585340454 -0.1829782834 0.5641310225
#> [351] 0.3169294122 -0.5464417046 0.0548117275 1.2736335696 -0.5813647525
#> [356] -1.0879195738 -0.9624215841 -1.7432428449 -0.6845659265 0.1401849188
#> [361] 0.8262421320 -1.2010774371 0.1069993459 0.5133881748 0.3360968725
#> [366] 1.2670725393 -0.3912736134 -0.0765423638 0.4812243068 0.5972742993
#> [371] -2.6849707310 -0.9067932563 0.0504359386 -1.9073760316 -1.3918561038
#> [376] -0.5581000410 -0.7833422116 3.3092854483 1.1718534019 2.1937288553
#> [381] -2.6781075222 -0.5072460165 -0.5876180661 0.1916383791 0.2266556978
#> [386] -0.1651416824 -0.0645110677 -1.4177148596 -1.4692117129 -1.3035174298
#> [391] -0.6466191658 -2.3088157318 0.1867549553 -0.1435895837 -0.1182882332
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