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

Abstract Details

Activity Number: 669
Type: Contributed
Date/Time: Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #306521
Title: Modeling of Zero-Inflated Count Data: Comparing the Results Using LOCF and MMRM
Author(s): Luyan Dai*+ and Moumita Sinha
Companies: Boehringer Ingelheim Pharmaceuticals, Inc. and Boehringer Ingelheim Pharmaceuticals, Inc.
Address: , , ,
Keywords: Zero Inflated Poisson model (ZIP) ; zero inflated generalized Poisson regression model (ZIGP) ; LOCF ; MMRM ; MCAR ; MAR
Abstract:

Poisson distribution is often not the optimal solution in count data as it assumes the mean and the variance are same. Also sometimes count data seem to have excessive zero values. We will compare the Poisson model, Zero inflated Poisson regression model (ZIP) and the zero inflated generalized Poisson regression model (ZIGP) using simulated data. When data is missing, last observation carried forward (LOCF) has been a very popular method in clinical trials. Recently mixed effect model repeated measures (MMRM) is gaining popularity as well. We will compare the results for the LOCF versus the MMRM approaches for different missing data mechanism for the various Poisson regression modeling described above.


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