Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model / 中华流行病学杂志

ABSTRACT

To evaluate the estimation of prevalence ratio (PR) by using bayesian log-binomial regression model and its application,we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software.The results showed that caregivers' recognition of infant's risk signs of diarrhea was associated significantly with a 13％ increase of medical care-seeking.Meanwhile,we compared the differences in PR's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1not adjusting for the covariates;model 2adjusting for duration of caregivers' education,model 3adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model.The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95％CI1.005-1.265),1.128(95％CI1.001-1.264)and 1.132(95％CI1.004-1.267),respectively.Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95％ CI1.055-1.206) and 1.126(95％ CI1.051-1.203),respectively,but the model 3 was misconvergence,so COPY method was used to estimate PR,which was 1.125 (95％CI1.051-1.200).In addition,the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model,but they had a good consistency in estimating PR.Therefore,bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.