Identification of inconsistent variates in factor analysis

DOI10.1007/BF02294262zbMath0826.62045OpenAlexW2036143930MaRDI QIDQ1897126

Publication date: 28 November 1995

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02294262

zbMATH Keywords

robustness likelihood ratio test factor analysis variable selection multiple comparisons likelihood principle inconsistent variates misspecified hypotheses

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Paired and multiple comparisons; multiple testing (62J15)

Related Items (4)

Simultaneous variable and factor selection via sparse group lasso in factor analysis ⋮ Stepwise variable selection in factor analysis ⋮ Variable selection via the weighted group lasso for factor analysis models ⋮ Variable selection for structural models

Uses Software

SAS
LISREL
EQS
BMDP
SAS/STAT

Cites Work

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Noniterative estimation and the choice of the number of factors in exploratory factor analysis
Linear latent variable models and covariance structures
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Selection of variables in two-group discriminant analysis by error rate and Akaike's information criteria
Factor analysis and AIC
A study of algorithms for covariance structure analysis with specific comparisons using factor analysis
Estimation of covariance structure models with parameters subject to functional restraints
Bayesian estimation in unrestricted factor analysis: A treatment for Heywood cases
On various causes of improper solutions in maximum likelihood factor analysis
Some contributions to maximum likelihood factor analysis
Analysis of Covariance Structures Under Elliptical Distributions
Asymptotic distributions in canonical correlation analysis and other multivariate procedures for nonnormal populations
Robustness of normal theory statistics in structural equation models*
Asymptotically distribution‐free methods for the analysis of covariance structures
Measures of multivariate skewness and kurtosis with applications
Linear Statistical Inference and its Applications
Robustness of normal theory methods in the analysis of linear latent variate models
A new look at the statistical model identification

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