Score Test for Dispersion in Generalized Inflation of Poisson Regression Model

• Main Authors: Yu-Che Tseng, 曾郁哲
• Other Authors: 張淑惠
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/47700423168430719811

碩士 === 國立臺灣大學 === 流行病學與預防醫學研究所 === 99 === A common problem in fitting count data with Poisson regression model is overdispersion, zero-inflation is one of the causes. Cox(1983) is the first one who proposed tests for the existence of overdispersion. Dean(1992) proposed another method. The reason that what Dean(1992) proposed is better than Cox(1983) is that Cox(1983) method proceeds tests without covariates, but Dean’s method did. In addition to the overdispersion problem, another statistical issue is underdispersion. When data show that variance is greater than mean, it is called overdispersion. In contrast, call underdispersion. Both types of data are called unequi-dispersed. Although many methods had been proposed to test overdispersion, limited methods have dealt with test for underdispersion using score test statistic and take into the account situations beyond zero-inflated over- or underdispersion. In this thesis, we use COM-Poisson distribution to derive unequi-dispersion test statistic, and extend the methods to other inflated cases, and conduct simulations to justify our methods.