MARGINAL MAXIMUM-LIKELIHOOD-ESTIMATION FOR THE ORDERED PARTITION MODEL
被引:8
作者:
WILSON, M
论文数: 0引用数: 0
h-index: 0
机构:
AUSTRALIAN COUNCIL EDUC RES,HAWTHORN,VIC 3122,AUSTRALIAAUSTRALIAN COUNCIL EDUC RES,HAWTHORN,VIC 3122,AUSTRALIA
WILSON, M
[1
]
ADAMS, RJ
论文数: 0引用数: 0
h-index: 0
机构:
AUSTRALIAN COUNCIL EDUC RES,HAWTHORN,VIC 3122,AUSTRALIAAUSTRALIAN COUNCIL EDUC RES,HAWTHORN,VIC 3122,AUSTRALIA
ADAMS, RJ
[1
]
机构:
[1] AUSTRALIAN COUNCIL EDUC RES,HAWTHORN,VIC 3122,AUSTRALIA
来源:
JOURNAL OF EDUCATIONAL STATISTICS
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1993年
/
18卷
/
01期
关键词:
D O I:
10.3102/10769986018001069
中图分类号:
G40 [教育学];
学科分类号:
040101 ;
120403 ;
摘要:
This article describes a marginal maximum likelihood (MML) estimation algorithm for Wilson's (1990) ordered partition model (OPM), a measurement model that does not require the set of available responses to assessment tasks to be fully ordered. The model and its estimation algorithm are illustrated through the analysis of an example data set. In the example, we use the ordered partition model to compare a set of alternative scoring schemes for open-ended science items.