Treatments of Missing Data: A Monte Carlo Comparison of RBHDI, Iterative Stochastic Regression Imputation, and Expectation-Maximization

This publication has 20 references indexed in Scilit:

• ML Estimation of Mean and Covariance Structures with Missing Data Using Complete Data Routines
  Journal of Educational and Behavioral Statistics, 1999
• Pairwise deletion for missing data in structural equation models: Nonpositive definite matrices, parameter estimates, goodness of fit, and adjusted sample sizes
  Structural Equation Modeling: A Multidisciplinary Journal, 1998
• COVARIANCE STRUCTURE ANALYSIS: Statistical Practice, Theory, and Directions
  Annual Review of Psychology, 1996
• Efficacy of the indirect approach for estimating structural equation models with missing data: A comparison of five methods
  Structural Equation Modeling: A Multidisciplinary Journal, 1994
• The Analysis of Social Science Data with Missing Values
  Sociological Methods & Research, 1989
• Effect on Secondary Data Analysis of Common Imputation Methods
  Sociological Methodology, 1989
• On Structural Equation Modeling with Data that are not Missing Completely at Random
  Psychometrika, 1987
• A Comparison of Methods for Treating Incomplete Data in Selection Research
  Educational and Psychological Measurement, 1987
• Estimation of Linear Models with Incomplete Data
  Sociological Methodology, 1987
• Estimation for Structural Equation Models with Missing Data
  Psychometrika, 1986