Generalized Residuals for General Models for Contingency Tables With Application to Item Response Theory

被引：18

作者：

Haberman, Shelby J. ^{[1
]}

Sinharay, Sandip ^{[1
]}

机构：

[1] Educ Testing Serv, Princeton, NJ 08541 USA

来源：

JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 2013年 / 108卷 / 504期

关键词：

Marginal distributions; Marginal estimation; Maximum likelihood; Normal approximations; Rasch model; Three-parameter logistic model; Two-parameter logistic model; MAXIMUM-LIKELIHOOD; CONDITIONAL ASSOCIATION; TESTS; FIT;

D O I：

10.1080/01621459.2013.835660

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：

Generalized residuals are a tool employed in the analysis of contingency tables to examine possible sources of model error. They have typically been applied to log-linear models and to latent-class models. A general approach to generalized residuals is developed for a very general class of models for contingency tables. To illustrate their use, generalized residuals are applied to models based on item response theory (IRT) models. Such models are commonly applied to analysis of standardized achievement or aptitude tests. To obtain a realistic perspective on application of generalized residuals, actual testing data are employed.

引用

页码：1435 / 1444

页数：10

共 63 条

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