Regression diagnostics for current status data using the odds-rate model

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Title:	Regression diagnostics for current status data using the odds-rate model
Other Titles:	使用優劣比-風險模型對現狀數據之迴歸診斷
Authors:	洪筱涵;Hung, Hsiao-Han
Contributors:	淡江大學數學學系碩士班温啟仲;Wen, Chi-Chung
Keywords:	現狀數據;優劣比-風險模型;配適度指標;Goodness of fit index;Current Status Data;Odds-rate model
Date:	2013
Issue Date:	2014-01-23 13:48:35 (UTC+8)
Abstract:	在進行迴歸分析之前，應先執行迴歸診斷，即對觀測數據評估迴歸模型的合適性。對於完整或右設限毀壞時間資料的迴歸診斷，許多的圖形法或量化法已被建立(如，Collett (1994), Klein and Moeschberger (2003), and Lawless (2003))。在本文中，對於現狀數據在優劣比-風險模型下，我們發展了評估比例風險假設和比例優劣比假設之診斷方法(Scharfstein, Tsiatis, and Gilbelt (1998))，同時對所提估計提供一穩定且快速計算法則。我們藉由模擬研究和三個實例分析來說明所提方法的表現。 The regression diagnostics that assess the adequacy of a regression model for observed data should be conducted before the regression analysis. For complete or right censored failure time data, several graphical or quantitative methods have been established for regression diagnostics (e.g. Collett (1994), Klein and Moeschberger (2003), and Lawless (2003)). In the thesis, we develop a diagnostic method for assessing the proportional hazards and proportional odds assumptions with current status data under the odds-rate model (Scharfstein, Tsiatis, and Gilbelt (1998)) and provide a stable and efficient computation method for proposed estimators. We illustrate the performance of our method via simulation studies and three real data analysis.
Appears in Collections:	[Graduate Institute & Department of Mathematics] Thesis

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