HGLM versus conditional estimators for the analysis of clustered binary data
Weechang Kang, Moo‐Song Lee, Youngjo Lee · Statistics in Medicine · 2005
Clustered binary data arise frequently in medical research such as cross-over clinical trials and twin studies. For the analysis of such data either a random-effects model or a conditional likelihood approach can be used. In this paper, we compare numerically the random-effects model estimator and the conditional likelihood estimator and discuss their relative merits for the analysis of binary data.