Which Random Effects Model?

Speaker’s Name: Professor Elena Kulinskaya and Ilyas Bakbergenuli

Speaker’s Institution: University of East Anglia

Random effects model (REM) in meta-analysis incorporates heterogeneity of effect measures across studies. We are interested in combining odds ratios from K 2×2 contingency tables. The standard (additive) REM is the random intercept model in 1-way ANOVA for log-odds ratios. Alternatively, heterogeneity can be induced via intra-cluster correlation, say assuming beta-binomial distributions. This (multiplicative) model is convenient for defining REM in conjunction with the Mantel-Haenzsel approach. Our method of estimating intra-class correlation (assumed constant across studies) is based on profiling the modified Breslow-Day test. Coverage of resulting confidence intervals is compared to standard methods through simulation.

Unexpectedly, we found that the standard methods are very biased in the multiplicative REM, and our new method is very biased in the standard REM. The explanation lies in the general (but new to us) fact that any function of a random variable is biased under REM.
The question on what exactly is random under REM is a difficult question for a frequentist…

Seminar Convenors: Andriy Olenko

AGR IT Support: Darren Condon