Maximum likelihood estimation of latent interaction effects with the LMS method

被引:1130
作者
Klein, A [1 ]
Moosbrugger, H [1 ]
机构
[1] Goethe Univ Frankfurt, D-6000 Frankfurt, Germany
关键词
latent interaction effects; mixture distribution; ML estimation; structural equation modeling (SEM); EM algorithm;
D O I
10.1007/BF02296338
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
In the context of structural equation modeling, a general interaction model with multiple latent interaction effects is introduced. A stochastic analysis represents the nonnormal distribution of the joint indicator vector as a finite mixture of normal distributions. The Latent Moderated Structural Equations (LMS) approach is a new method developed for the analysis of the general interaction model that utilizes the mixture distribution and provides a ML estimation of model parameters by adapting the EM algorithm. The finite sample properties and the robustness of LMS are discussed. Finally, the applicability of the new method is illustrated by an empirical example.
引用
收藏
页码:457 / 474
页数:18
相关论文
共 35 条
[1]  
ABRAMOWITZ M, 1971, HDB MATH FUNCTIONS
[2]  
Aiken L. S., 1991, MULTIPLE REGRESSION
[3]  
[Anonymous], 1975, APPL MULTIPLE CORREL
[4]  
[Anonymous], 1998, FRANKFURTER KORPERKO
[5]  
Arbuckle J. L., 1997, AMOS USERS GUIDE VER
[6]  
Bentler PM., 1993, EQS WINDOWS USERS GU
[7]  
Bentler PM, 2006, EQS 6 structural equations program manual
[8]   An alternative two stage least squares (2SLS) estimator for latent variable equations [J].
Bollen, KA .
PSYCHOMETRIKA, 1996, 61 (01) :109-121
[9]  
BOLLEN KA, 1995, SOCIOLOGICAL METHOLO, P25
[10]   TENACIOUS GOAL PURSUIT AND FLEXIBLE GOAL ADJUSTMENT - EXPLICATION AND AGE-RELATED ANALYSIS OF ASSIMILATIVE AND ACCOMMODATIVE STRATEGIES OF COPING [J].
BRANDTSTADTER, J ;
RENNER, G .
PSYCHOLOGY AND AGING, 1990, 5 (01) :58-67