在公共衛生、社會科學、工程科學及農業學等領域中,經常使用卜瓦松分配來分析離散計數型資料,但該類型資料時常會有過多某特定值事件發生的問題 (如零事件) ,進而造成過度分散 (over-dispersion) 的情形。因此Lambert (1992) 提出零膨脹卜瓦松迴歸模型 (zero-inflated Poisson regression; ZIP) 來配適零膨脹資料。 本篇論文將零膨脹卜瓦松迴歸模型擴展為零K膨脹卜瓦松迴歸模型 (zero-and-K inflated Poisson regression; ZKIP) 。此一模型可應用於包含過多零值與K值的計數型資料中,其中K為非零的正整數。例如,一份探討兩年內青壯年人口看牙醫次數的調查中,大多數人看牙醫次數為零次 (零值) 或壹次 (K值為壹) ,即所謂零K膨脹。 本論文在模擬研究中,將零K膨脹卜瓦松迴歸模型和零膨脹卜瓦松迴歸模型以及一般卜瓦松迴歸模型進行比較。分別在卜瓦松分配、零膨脹卜瓦松分配及零K膨脹卜瓦松分配生成的資料中,探討各模型資料配適的優劣性,以及討論這些統計方法使用的時機。本論文同時探討樣本數、零膨脹率、K膨脹率及卜瓦松分配平均數對模型配適的影響。 模擬研究結果顯示,在不同的樣本數、零膨脹率、K膨脹率及卜瓦松分配平均數下,零K膨脹卜瓦松迴歸模型有較佳表現。在實證研究中,以2005年的「國民健康訪問調查」 (National Health Interview Survey, NHIS) 資料,探討卜瓦松、零膨脹卜瓦松以及零K膨脹卜瓦松三種迴歸模型配適實際資料的情況。研究結果顯示,本論文所提出的零K膨脹卜瓦松迴歸模型得到較佳的配適。
In the public health, social science, engineering science, agricultural science and other disciplines, it is common to use the Poisson (POI) regression to analyze discrete count data. However, excessive zeros often occur in the data and then cause over-dispersion. Therefore, Lambert (1992) proposed the zero-inflated Poisson (ZIP) regression model to fit such data. In this research, we extend the zero-inflated Poisson regression model to the zero-and-K-inflated Poisson (ZKIP) regression model. The ZKIP model can be applied to count data, which contains extra zeros and Ks, where K is a non-zero positive integer. For example, a survey question inquiring the number of times that young adults visited a dentist in two years resulted in zero time (zero) or one time (K) for most people, this is so-called zero-and-K-inflated data. In the simulation study, it compares the goodness of fit for ZKIP, ZIP and POI models, and discusses the best timing of using these models in the data. We also explores the effect of different sample size, zero proportion, k proportion and mean in Poisson distribution on data fitting for these considered models The simulation study shows that ZKIP has better fit than POI and ZIP in all simulation configurations. In the empirical study, we use 2005 national health interview survey data to compare the performance of data fitting for the three models. The results show that the zero-and-K-inflated Poisson regression model outperforms the other two models.