Functions for estimation and multiple imputation from incomplete multivariate data under a normal model
The norm2 package provides functions for analyzing incomplete
multivariate
data using techniques and algorithms described by Schafer (1997). The
name of this package derives from the assumed model for the complete
data, which is a multivariate normal model. The
major functions are:
emNorm EM algorithm estimating model parameters mcmcNorm MCMC algorithm for simulating parameters and missing values impNorm Simulate or predict missing values loglikNorm Loglikelihood function logpostNorm Log-posterior density function miInference Combine results from analyses after multiple imputation
The package also includes three datasets:
cholesterol Cholesterol levels for heart-attack patients flas Foreign Language Attitude Scale marijuana Changes in heart rate after marijuana use
Schafer, J.L. (1997) Analysis of Incomplete Multivariate Data. London: Chapman & Hall/CRC Press.
For more information about functions in
norm2, see User's Guide for norm2
in the library subdirectory doc.