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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.

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Spelling suggestions: "subject:"quasilikelihood estimate"" "subject:"quasilikelihood stimate""

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具有額外變異之離散型資料分析探討 / A Study on Modelling Overdispersion in Categorical Data

陳麗如 Unknown Date (has links)
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.
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

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