seqLlh: Inference using MI-based sequential based method, under J2R

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

Description

For a given dataset with monotone missingness, impute the missing data from the conditional distribution given observed under J2R by proper MI, output the imputed dataset

Usage

seqLlh(
  seq_formula,
  data_wide,
  trt_name,
  M,
  fit_model,
  id_name,
  method = "PMM",
  bootstrap = FALSE,
  B = 100
)

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)
id_name	name of the id variable
method	name of the likelihood-based method. Available: PMM, CBMI
bootstrap	Whether to use bootstrap variance
B	the number of bootstrap replicate

Value

Point estimation and variance estimation obtained by delta method:

• llh_estpoint estimate

• var_llhvariance estimate approximated by delta method

• var_bootvariance estimate approximated by delta method

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