Craig K. Enders

A Primer on Maximum Likelihood Algorithms Available for Use With Missing Data

Abstract Maximum likelihood algorithms for use with missing data are becoming commonplace in microcomputer packages. Specifically, 3 maximum likelihood algorithms are currently ...

Using the Expectation Maximization Algorithm to Estimate Coefficient Alpha for Scales With Item-Level Missing Data.

A 2-step approach for obtaining internal consistency reliability estimates with item-level missing data is outlined. In the 1st step, a covariance matrix and mean vector are obt...

Applied Missing Data Analysis

Part 1. An Introduction to Missing Data. 1.1 Introduction. 1.2 Chapter Overview. 1.3 Missing Data Patterns. 1.4 A Conceptual Overview of Missing Data heory. 1.5 A More Formal De...

The impact of nonnormality on full information maximum-likelihood estimation for structural equation models with missing data.