具有隨機效應及測量誤差之邏輯斯迴歸模型的參數估計方法

The Estimation of the Logistic Regression Model with Measurement Errors and Random Effects

林承翰(Cherng-Hann Lin)

指導教授 ： 黃逸輝

淡江大學/理學院/數學學系碩士班/碩士(2013年)

https://doi.org/10.6846/TKU.2013.00681

摘要

在過去文獻中很少討論在廣義線性模式中同時有測量誤差和隨機效用，主要是因為將隨機效用積分後的分配已不是廣義線性模式，使得傳統上的條件分數法或是校正分數法難以應用。本文主要探討邏輯斯迴歸在有測量誤差和隨機效用時的模型中，使用部分條件分數估計方法，並與 Naive 及迴歸校正法兩者作比較。

關鍵字

測量誤差 ； 隨機效應 ； 邏輯斯模型 ； 條件分數法

並列摘要

There are not many literatures discuss the statistical inference when the measurement error and random effect exist in the generalized linear model. The main reason is that the distribution after integrating the random effect is no longer a generalized linear model, hence the conventional conditional score or corrected score are difficult in application. This paper discussed the estimation method when measurement error and random effect coexist in the logistic regression model, the estimation was done by a partially conditional score. We compare the efficient of the methods of Naive and regression calibration with the proposed method by simulation studies.

並列關鍵字

Measurement error ； Random effect ； Logistic model ； Conditional score

參考文獻

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Stefanski, L. A. and Carroll, R. J. (1987). Conditional Scores and Optimal Scores for Generalized Linear Measurement Error Models. Biometrika, V. 74, No. 4, 703-716.

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