Online Program

Maximum likelihood estimates by Homogenous log-linear models for three-way contingency tables with Missing data with application to neuropathology data

Tuesday, November 3, 2015

Haresh Rochani, DrPH, MPH , M.B.B.S., Department of BIo-statistics, Georgia Southern University, Statesboro, GA
Robert Vogel, Professor, Department of BIo-statistics, Georgia Southern University, Statesboro, GA
Hani Samawi, PhD, P.O.Box 8015, Jiann-Ping Hus College of Public Health, Georgia Southern University, Statesboro, GA
Daniel Linder, PhD, Department of Biostatistics, Georgia Southern University, Statesboro, GA
Missing observations in cross-classified data are an extremely common problem in the process of research in clinical studies, observational studies and public health. Ignorance of missing values in the analysis can produce biased results and low statistical power. The focus of this research is to expand Baker, Rosenberger and Dersimonian (BRD) model approach to compute the explicit maximum likelihood estimates for cell counts for three-way cross-classified data. In case of missing observations, derivation of explicit cell counts for three-way table with supplementary margins can be obtained by controlling the missingness in third variable and by modeling the missing-data indicators using homogeneous log-linear models. Previous methods for contingency tables with supplementary margins required an iterative algorithm, however, expected cell counts for complete cells as well as missing cells can be obtained by simple algebraic formula. We conduct a simulation study with Neuropatholody data to illustrate that the explicit maximum likelihood estimates can produce consistent results.

Learning Areas:

Basic medical science applied in public health
Biostatistics, economics
Other professions or practice related to public health
Public health or related research

Learning Objectives:
Demonstrate the application of log-linear models for contingency tables with missing data. Analyze the categorical data with missing observations.

Keyword(s): Biostatistics, Dementia

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I have been working in Bio-statistics field for last 30 years.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.