Fitting the Rasch Model under the Logistic Regression Framework to Reduce Estimation Bias

被引：0

作者：

Pan, Tianshu ^{[1
]}

机构：

[1] Pearson, San Antonio, TX 78259 USA

来源：

JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2018年 / 17卷 / 01期

关键词：

The Rasch model; logistic regression; maximum likelihood; penalized maximum likelihood;

D O I：

10.22237/jmasm/1530028025

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The purpose of this study was to show how and why the Rasch model can be fitted under the logistic regression framework. Then a penalized maximum likelihood (Firth, 1993) for logistic regression models can be used to reduce ML biases when fitting the Rasch model. These conclusions are supported by a simulation study.

引用

页码：1 / 15

页数：14

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