Joseph L. Schafer

Analysis of Incomplete Multivariate Data

Analysis of Incomplete Multivariate Data

Introduction Assumptions EM and Inference by Data Augmentation Methods for Normal Data More on the Normal Model Methods for Categorical Data Loglinear Models Methods for Mixed D...

A comparison of inclusive and restrictive strategies in modern missing data procedures.

Two classes of modern missing data procedures, maximum likelihood (ML) and multiple imputation (MI), tend to yield similar results when implemented in comparable ways. In either...

Robustness of a multivariate normal approximation for imputation of incomplete binary data

Abstract Multiple imputation has become easier to perform with the advent of several software packages that provide imputations under a multivariate normal model, but imputation...

A comparison of inclusive and restrictive strategies in modern missing data procedures.

On the performance of random‐coefficient pattern‐mixture models for non‐ignorable drop‐out

Abstract Random‐coefficient pattern‐mixture models (RCPMMs) have been proposed for longitudinal data when drop‐out is thought to be non‐ignorable. An RCPMM is a random‐effects m...