title: [Application of zero-inflated models on regression analysis of count data: a study of sub-health symptoms].
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 α 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, O = 308.011, P < 0.001, s(2)>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.
authors.affiliation: Cardiovascular Institute and Fuwai Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Xu
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.forename: Tao
authors.initials: T
authors.lastname: Chen
mesh_terms: D006801:Humans; D015233:Models, Statistical; D011336:Probability; D012044:Regression Analysis