The comparison of logistic regression models, on analyzing the predictors of health of adolescents, having multinomial response in Jimma Zone South-west Ethiopia

Self- reported health status is the most commonly used measures of subjective and global measure of health because it is simple, economical and easy to administer. The objective of the study is to compare the performance of logistic regression models having multinomial response and identify the factors affecting health status of adolescents. Based on two stage sampling technique 2084 adolescents were interviewed to study the health status of teenagers in Jimma zone. In this article, we reviewed the most important logistic regression model and common approaches used to verify goodness-of-fit, using software R. We performed formal as well as graphical analyses to compare ordinal logistic regression models using data sets of health status. The results obtained from both baseline category logit model and ordinal logistic regression showed that sex of adolescents, source of drinking water and educational status significantly affect health status of teenagers. It was also found that a cumulative logit model containing these predictors provided the best description of the dataset among baseline category logit model, adjacent category logit model and continuation ratio model. Key words: Adolescents’ health status, multinomial logistic regression and ordinal logistic regression models, model comparisons using Akakie information criteria (AIC), goodness of fit.