Application of zero-inflated models on regression analysis of count data: a study of sub-health symptoms / 中华流行病学杂志

ABSTRACT

To explore the goodness of fit about the zero-inflated (ZI) models in analyzing data related to sub-health symptoms in which the counts are non-negative integers. ZI models are conducted with Stata 11.0. The coefficient of a, Vuong test, O test and likelihood test are used to compare the goodness of fit for ZI models with the common used models such as passion model,negative binomial model. When a is 0.939, and the Z statistic of Vuong test is 32.08, P＜0.0001,which shows that there are too many zeros. The mean number of sub-health symptoms is 2.90, s=3.85, 0=308.011, P＜0.001, s2＞(-x), indicating that the data are over-dispersed. In addition, the optimum goodness of fit is found in zero-inflated negative binomial (ZINB) model with the largest log likelihood and the smallest AIC. ZINB seems the optimal model to study those over-dispersed count data with too many zeros.