机构:
Univ London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, EnglandUniv London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, England
Moustaki, I
[1
]
Knott, M
论文数: 0引用数: 0
h-index: 0
机构:
Univ London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, EnglandUniv London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, England
Knott, M
[1
]
机构:
[1] Univ London London Sch Econ & Polit Sci, Dept Stat, London WC2A 2AE, England
generalized linear models;
latent trait model;
EM algorithm;
scoring methods;
D O I:
10.1007/BF02296153
中图分类号:
O1 [数学];
学科分类号:
0701 ;
070101 ;
摘要:
In this paper we discuss a general model framework within which manifest variables with different distributions in the exponential Family can be analyzed with a latent trait model. A unified maximum likelihood method For estimating the parameters of the generalized latent trait model will be presented. We discuss in addition the scoring of individuals on the latent dimensions. The general framework presented allows, not only the analysis of manifest variables all of one type but also the simultaneous analysis of a collection of variables with different distributions. The approach used analyzes the data as they are by making assumptions about the distribution of the manifest variables directly.