A review of techniques for treating missing data in OM survey research
Top Cited Papers
- 12 May 2005
- journal article
- review article
- Published by Wiley in Journal of Operations Management
- Vol. 24 (1) , 53-62
- https://doi.org/10.1016/j.jom.2005.03.001
Abstract
No abstract availableKeywords
This publication has 34 references indexed in Scilit:
- Multiple Imputation for Missing Data: Making the most of What you KnowOrganizational Research Methods, 2003
- Longitudinal Modeling with Randomly and Systematically Missing Data: A Simulation of Ad Hoc, Maximum Likelihood, and Multiple Imputation TechniquesOrganizational Research Methods, 2003
- Techniques for improving response rates in OM survey researchJournal of Operations Management, 2002
- Estimation of a Duration Model in the Presence of Missing DataThe Review of Economics and Statistics, 1999
- Missing Data in Likert Ratings: A Comparison of Replacement MethodsThe Journal of General Psychology, 1998
- Extensions of estimation methods using the EM algorithmJournal of Econometrics, 1991
- [Missing-Data Adjustments in Large Surveys]: CommentJournal of Business & Economic Statistics, 1988
- Analyzing Marketing Research Data with Incomplete Information on the Dependent VariableJournal of Marketing Research, 1987
- Alternative Approaches to Missing Values in Discriminant AnalysisJournal of the American Statistical Association, 1976
- The Treatment of Missing Values in Discriminant Analysis-1. The Sampling ExperimentJournal of the American Statistical Association, 1972