在統計分析方法中，計數模式（例如：Poisson Regression Model、Negative Binomial RegressionModel、Zero-inflated Regression Model）已被廣泛應用於心理學、 管理學，以及其他社會科學等領域。不過，國內相關研究一直未將現代測驗理論之 試題反應理論（Item Response Theory, IRT）模式與這些計數模式相結合，也就是未 能以IRT 的觀點：受試者潛在特質和試題難度，對於計數資料過度離散（Over-dispersion） 或零膨脹（Zero-inflated）等異常現象提出解釋與處理。因此，本研究結 合Rasch 模式與計數模式提出Rasch-ZINB 迴歸模式、Rasch-ZIG 迴歸模式，以及 Rasch-ZIP 迴歸模式，並以某學科考試結果做為模式分析之實例。整體而言，本研 究提出的結合模式，針對資料異常現象，可以藉由受試者潛在特質和試題難易度加 以解釋。最後，進行模擬分析以更確認研究結果的可信度，並提出未來研究的一些 建議。

Count data models (for example, Poisson regression model, negative binomial regression model, and zero-inflated regression model) have been widely applied in psychology, management and other social science fields. However, related studies in Taiwan have been failed to make connection between item response theory (IRT) and count data models which means those studies can’t propose explanation from IRT approaches under the over-dispersion and zero-inflated count data. As a result, this study integrate Rasch model with count data model in order to propose a Rasch-ZINB regression model, Rasch-ZIG regression model, and Rasch-ZIP regression model. Various statistical tests for model evaluation are illustrated through an example of statistic testing. Overall, the integration model proposed in this study can make further explanations on data’s skew phenomenon by means of item psychmetric features and individual traits. Finally, some suggestions for future research are provided.