rr_seq_imp: Sequential imputation

In Merck/mmrm: Mixed model repeated measures and its extension

Description

For a given dataset with monotone missingness, conduct sequential imputation based on linear / robust / rank regression

Usage

rr_seq_imp(
  seq_formula,
  data_wide,
  trt_name,
  M,
  fit_model,
  estimator = "reg with interaction"
)

Arguments

seq_formula	a list of formulas for sequential regression
data_wide	wide-form of the data frame
trt_name	name of the treatment variable
M	imputation size
fit_model	type of the analysis model. Available: lm, Rfit::rfit (rank regression), MASS::rlm (robust regression)
estimator	type of the estimator. Available: sample mean, reg with interaction, reg without interaction

Value

Rubin's point and variance estimate

• ate_estMI point estimation of the ATE

• var_rubinMI variance estimation by Rubin's rule

Merck/mmrm documentation built on Dec. 17, 2021, 4:12 a.m.