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Title:	具有額外變異之離散型資料分析探討 A Study on Modelling Overdispersion in Categorical Data
Authors:	陳麗如
Contributors:	江振東陳麗如
Keywords:	額外變異廣義線性模型準概似估計模型隨機效果模型 Overdispersion General Linear Model Quasi-Likelihood Estimate Random-Effect Model
Date:	2001
Issue Date:	2016-04-15 16:10:23 (UTC+8)
Abstract:	處理類別型的資料時，常由於變異數與平均數間具有函數關係，因此資料呈現出來的變異程度會比預期的變異程度來的大，這種現象就稱為資料具有額外變異。一般的分析方法是利用廣義線性模型先作估計，再對估計之標準誤做調整。本文中將探討處理額外變異的另外兩種方法—準概似估計和隨機效果模型，並分別利用紡織原料與毒物學研究之資料作為範例來比較此兩種方法與前者的異同。 Overdispersion is a common phenomenon in practice when modelling categorical data, and the scaled Pearson chi-square is usually used to measure it. In this study, we examine two other methods—the quasi-likelihood and the random-effect models. In addition, two examples are provided for illustration.
Reference:	Abramowitz, M. and Stegun, I. A.（1972）, Handbook of Mathematical Functions with Formulas, Graphs and Mathematical Tables, U.S. Government Printing Office, Washington. Agresti, A. (1990), Categorical Data Analysis, New York: Wiley. Agresti, A. (1996), An introduction to Categorical Data Analysis, New York: Wiley. Box, G.E.P. and Cox, D.R.（1964）, “An analysis of transformation（with discussion）,” J. R. Statist. Soc B 26, 211-43. Collett, D. (1991), Modelling Binary Data, London : Chapman & Hall. MathSoft, Inc.（1999）, S-PLUS 2000 Guide to Statistics, Volume 1, Data Analysis Products Division, MathSoft, Seattle, WA. Morgan, B.J.T. (1992), Analysis of Quantal Response Data, London: Chapman & Hall. Nelder, J.A. and Pregibon, D. (1987), “An extended quasi-likelihood function,” Biometrika, 74, 221-231. Wedderburn, R.W.M. (1974), “Quasi-likelihood functions, generalized linear models and the Gauss-Newton method,” Biometrika, 61, 439-447.
Description:	碩士國立政治大學統計學系 88354021
Source URI:	http://thesis.lib.nccu.edu.tw/record/#A2002001358
Data Type:	thesis
Appears in Collections:	[Department of Statistics] Theses

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