Modelling non-ignorable missing-data mechanisms with item response theory models

被引：0
|
作者：
Holman, R
Glas, CAW
机构：
[1] Amsterdam Med Ctr, Dept Clin Epidemiol & Biostat, Amsterdam, Netherlands
[2] Univ Twente, Dept Educ Measurement & Data Anal, NL-7500 AE Enschede, Netherlands
来源：
BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY | 2005年 / 58卷
关键词：
D O I：
暂无
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
A model-based procedure for assessing the extent to which missing data can be ignored and handling non-ignorable missing data is presented. The procedure is based on item response theory modelling. As an example, the approach is worked out in detail in conjunction with item response data modelled using the partial credit and generalized partial credit models. Simulation studies are carried out to assess the extent to which the bias caused by ignoring the missing-data mechanism can be reduced. Finally, the feasibility of the procedure is demonstrated using data from a study to calibrate a medical disability scale.
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页码：1 / 17
页数：17
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