Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model / 中华流行病学杂志
Chinese Journal of Epidemiology
;
(12): 400-405, 2017.
Artículo
en Chino
| WPRIM
| ID: wpr-737654
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.
Texto completo:
Disponible
Índice:
WPRIM (Pacífico Occidental)
Tipo de estudio:
Estudio de prevalencia
Idioma:
Chino
Revista:
Chinese Journal of Epidemiology
Año:
2017
Tipo del documento:
Artículo
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