Covariate adjusted glm model

Usage

robin_glm(
  formula,
  data,
  treatment,
  contrast = "difference",
  contrast_jac = NULL,
  vcov = "vcovG",
  family = gaussian(),
  vcov_args = list(),
  pair,
  ...
)

Arguments

formula: (formula) A formula of analysis.
data: (data.frame) Input data frame.
treatment: (formula or character(1)) A formula of treatment assignment or assignment by stratification, or a string name of treatment assignment.
contrast: (function or character(1)) A function to calculate the treatment effect, or character of "difference", "risk_ratio", "odds_ratio" for default contrasts.
contrast_jac: (function) A function to calculate the Jacobian of the contrast function. Ignored if using default contrasts.
vcov: (function) A function to calculate the variance-covariance matrix of the treatment effect, including vcovHC and vcovG.
family: (family) A family object of the glm model.
vcov_args: (list) Additional arguments passed to vcov.
pair: Pairwise treatment comparison.
...: Additional arguments passed to glm or glm.nb.

Details

If family is MASS::negative.binomial(NA), the function will use MASS::glm.nb instead of glm.

Examples

robin_glm(
  y ~ treatment * s1,
  data = dummy_data,
  treatment = treatment ~ s1, contrast = "difference"
)
#> Model        :  y ~ treatment * s1 
#> Randomization:  treatment ~ s1  ( Simple )
#> Variance Type:  vcovG 
#> Marginal Mean: 
#>      Estimate  Std.Err    2.5 % 97.5 %
#> pbo  0.223048 0.068366 0.089054 0.3570
#> trt1 0.763992 0.077178 0.612727 0.9153
#> trt2 0.948275 0.077437 0.796502 1.1000
#> 
#> Contrast     :  h_diff
#>                Estimate Std.Err Z Value  Pr(>|z|)    
#> trt1 v.s. pbo   0.54094 0.10282  5.2611 1.432e-07 ***
#> trt2 v.s. pbo   0.72523 0.10302  7.0399 1.924e-12 ***
#> trt2 v.s. trt1  0.18428 0.10911  1.6890   0.09123 .  
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1