ESTIMATION FOR THE MULTIPLE FACTOR MODEL WHEN DATA ARE MISSING

被引：111

作者：

FINKBEINER, C

机构：

[1] Invorydale Technical Center, 3W76, The Procter and Gamble Co., Cincinnati, 45217, Ohio

来源：

PSYCHOMETRIKA | 1979年 / 44卷 / 04期

关键词：

factor analysis; missing data;

D O I：

10.1007/BF02296204

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

A maximum likelihood method of estimating the parameters of the multiple factor model when data are missing from the sample is presented. A Monte Carlo study compares the method with 5 heuristic methods of dealing with the problem. The present method shows some advantage in accuracy of estimation over the heuristic methods but is considerably more costly computationally. © 1979 The Psychometric Society.

引用

页码：409 / 420

页数：12

共 23 条

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