4. Regression with Missing Ys: An Improved Strategy for Analyzing Multiply Imputed Data
Abstract
When fitting a generalized linear model -- such as a linear regression, a logistic regression, or a hierarchical linear model -- analysts often wonder how to handle missing values of the dependent variable Y. If missing values have been filled in using multiple imputation, the usual advice is to use the imputed Y values in analysis. We show, however, that using imputed Ys can add needless noise to the estimates. Better estimates can usually be...
Paper Details
Title
4. Regression with Missing Ys: An Improved Strategy for Analyzing Multiply Imputed Data
Published Date
Aug 1, 2007
Journal
Volume
37
Issue
1
Pages
83 - 117
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