多元羅吉斯迴歸模型常被用於推論風險因子與多個類別疾病之間的關係。本文利用累積分配函數的無母數最大概似估計量與其半參數最大概似估計量的差，提出一個Kolmogorov-Smirnov形式檢定統計量，以檢測病例對照研究下多元羅吉斯迴歸模型的適合度，並使用拔靴法計算檢定統計量的p-值。本文亦透過一些模擬研究以評估該檢定的型一誤比率與檢定力。最後將Kolmogorov-Smirnov形式檢定統計量應用於實際資料示範。 The multinomial logistic regression model is used popularly for inferring the relationship of risk factors and disease with multiple categories. This thesis bases on the discrepancy between the nonparametric maximum likelihood estimator and semiparametric maximum likelihood estimator of the cumulative distribution function to propose a Kolmogorov-Smirnov type test statistic to assess adequacy of the multinomial logistic regression model for case-control data. A bootstrap procedure is presented to calculate the p-value of the proposed test statistic. Empirical type I error rates and powers of the test are evaluated by simulation studies. Some examples will be illustrated the implementation of the test.
