This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 638
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract - #306915
Title: Penalized EM in Binomial Models with Missing Categorical Covariates
Author(s): John R. Stevens*+ and Jeremiah Rounds and David I. Schlipalius
Companies: Utah State University and Purdue University and Queensland Government
Address: 3900 Old Main Hill, Logan, UT, 84322-3900,
Keywords: Expectation-Maximization ; Firth's Penalized Maximum Likelihood ; Incomplete Data ; Rhyzopertha dominica ; Separation of Points

In a dose-response study involving pesticide application, a categorical covariate was only recorded for surviving pests. In such cases, traditional maximum likelihood approaches alone cannot provide useful inference. An additional complication in these data is the possible separation of points, resulting in impractically large standard errors. We present an EM-based solution to missing categorical covariates in binomial models with logit links, addressing the separation of points by the use of a method of moments estimator for Firth's bias-reduction score-modification. We simulate to address questions about estimate bias, distribution, and appropriate coverage by confidence intervals.

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