Estimates for cell counts and common odds ratio in three-way contingency tables by homogeneous log-linear models with missing data
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- 作者：Haresh D. Rochani ; Robert L. Vogel ; Hani M. Samawi…
- 关键词：Contingency table ; Cross ; classified data ; Log ; linear model ; Maximum likelihood method ; Missing data ; Common odds ratio ; Three ; way table
- 刊名：AStA Advances in Statistical Analysis
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：101
- 期：1
- 页码：51-65
- 全文大小：
- 刊物类别：Mathematics and Statistics
- 刊物主题：Statistics, general; Statistics for Business/Economics/Mathematical Finance/Insurance; Probability Theory and Stochastic Processes; Econometrics;
- 出版者：Springer Berlin Heidelberg
- ISSN：1863-818X
- 卷排序：101
文摘
Missing observations often occur in cross-classified data collected during observational, clinical, and public health studies. Inappropriate treatment of missing data can reduce statistical power and give biased results. This work extends the Baker, Rosenberger and Dersimonian modeling approach to compute maximum likelihood estimates for cell counts in three-way tables with missing data, and studies the association between two dichotomous variables while controlling for a third variable in \( 2\times 2 \times K \) tables. This approach is applied to the Behavioral Risk Factor Surveillance System data. Simulation studies are used to investigate the efficiency of estimation of the common odds ratio.