IPW and Mean Score Methods for Time-Course Missing Data
Fit a geeglm model using AIPW
Fit a geeglm model using meanScore
Fit a geeglm model using miAIPW
Fit a geeglm model using miSIPW
print method for ipw
print method for meanscore
Model Selection criteria QIC
Fit a geeglm model using SIPW
summary method for ipw
summary method for meanscore
internal function for updating alpha
internal function for updating beta through Fisher Scoring
internal function for updating scale parameter
internal function for sandwich estimator
Contains functions for data analysis of Repeated measurement using GEE. Data may contain missing value in response and covariates. For parameter estimation through Fisher Scoring algorithm, Mean Score and Inverse Probability Weighted method combining with Multiple Imputation are used when there is missing value in covariates/response. Reference for mean score method, inverse probability weighted method is Wang et al(2007)<doi:10.1093/biostatistics/kxl024>.