Covariate adjusted glm model

Usage

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

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.
...: 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"
)
#> Treatment Effect
#> -------------
#> Model        :  y ~ treatment * s1 
#> Randomization:  treatment ~ s1 
#> Marginal Mean: 
#> counter-factual prediction
#> 
#>       pbo      trt1      trt2 
#> 0.2230481 0.7639923 0.9482753 
#> 
#> Marginal Mean Variance: 
#>        pbo       trt1       trt2 
#> 0.06836557 0.07717784 0.07743670 
#> 
#> 
#> Variance Type:  vcovG 
#>             Estimate Std.Err Z Value Pr(>|z|)    
#> trt1 - pbo     0.541   0.103    5.26  1.4e-07 ***
#> trt2 - pbo     0.725   0.103    7.04  1.9e-12 ***
#> trt2 - trt1    0.184   0.109    1.69    0.091 .  
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1