泊松分布
混合模型
统计
伯努利原理
贝叶斯概率
纵向数据
计量经济学
度量(数据仓库)
比例(比率)
选型
数学
泊松回归
计算机科学
伯努利审判
贝叶斯信息准则
数据挖掘
地理
人口
医学
环境卫生
工程类
航空航天工程
地图学
作者
Bobby L. Jones,Daniel S. Nagin,Kathryn Roeder
标识
DOI:10.1177/0049124101029003005
摘要
This article introduces a new SAS procedure written by the authors that analyzes longitudinal data (developmental trajectories) by fitting a mixture model. The TRAJ procedure fits semiparametric (discrete) mixtures of censored normal, Poisson, zero-inflated Poisson, and Bernoulli distributions to longitudinal data. Applications to psychometric scale data, offense counts, and a dichotomous prevalence measure in violence research are illustrated. In addition, the use of the Bayesian information criterion to address the problem of model selection, including the estimation of the number of components in the mixture, is demonstrated.
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