The meta-analysis of rare binary data is a difficulty in the field of medical research, and its methodology remains immature. The traditional meta-analysis technique is based on the normal-normal model of fixed effects analysis or random-effects analysis, however there are methodological problems in this method. Stijnen proposed an exact within-study likelihood models (EWLM) meta-analysis technique based on the generalized linear mixed model (GLMM), including the binomial-normal model (BN) and Hypergeometric-normal model (HNM), which can be used to achieve random effects meta-analysis of rare binary data. This paper introduces the model in detail and its implementation in SAS software with examples to provide relevant SAS code.
