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Multivariate logistic regression with incomplete covariate and auxiliary information

Sanjoy K Sinha1, Nan M Laird, Garrett M Fitzmaurice

  • 1School of Mathematics and Statistics, Carleton University, Ottawa, ON, Canada sinha@math.carleton.ca.

Journal of Multivariate Analysis
|October 19, 2010
PubMed
Summary

This study introduces a multivariate logistic regression model to improve analysis of multiple binary outcomes with missing covariate data. Utilizing auxiliary information significantly enhances the efficiency of regression estimators, especially with correlated outcomes.

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