100年第2學期-4854 類別資料分析 課程資訊
|Midterm, Quizzes, or Projects||40|
Introducing advanced statistical models and theories for categorical data used by statistical researchers and practitioners.
Categorical data analysis that deals with qualitative or discrete quantitative data is one of the most important statistical tools nowadays. In recent years, this tool plays a fundamental role on analyzing polychotomous data, particularly in the social and health sciences. This course introduces statistical theories and models for analyzing categorical data. The main topics cover :
(1) likelihood-based inferences on measures of association for two-dimensional and three-dimensional contingency tables under different assumptions. (2) generalized linear (mixed) models with emphasis on binary (Poisson) regression and logit models. (3) Repeated categorical data modeling, such as generalized estimating equation approaches and quasi-likelihood methods. (4) Asymptotic results and other advanced topics.