misaem is a package to perform linear regression and logistic regression with missing data, under MCAR (Missing completely at random) and MAR (Missing at random) mechanisms. The covariates are assumed to be continuous variables. The methodology implemented is based on maximization of the observed likelihood using EM-types of algorithms. It has been written by Wei Jiang (former maintainer) and Julie Josse (current maintainer). The package includes:
- Parameters estimation.
- Estimation of standard deviation for estimated parameters.
- Model selection procedure based on BIC.