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Factor Analysis and AIC

Psychometrika, 1987
The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis.
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FACTOR INTERACTION IN NONLINEAR FACTOR ANALYSIS

British Journal of Mathematical and Statistical Psychology, 1967
Factor interaction models are defined as those cases in nonlinear factor analysis in which the specification equation contains products of two or more latent variables or functions of latent variables. A complete algebraic treatment is given for the case of a product of two latent variables, and certain more general cases are briefly outlined.
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Profile Factor Analysis and Variable Factor Analysis

Psychological Reports, 1964
Nunnally (1962) mentions three types of profile factor analyses: correlational, covariance, and raw score sums of crossproducts. When principal components factors are used, each of these profile analyses corresponds to a precisely equivalent factor analysis of variables.
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Factor Analysis

2021
Klaus Backhaus   +4 more
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Longitudinal Factor Analysis

Psychometrika, 1970
A model is presented for factor analysing scores on a set of psychological tests administered as both pre- and postmeasures in a study of change. The model assumes that the same factors underlie the tests on each occasion, but that factor scores as well as factor loadings may change between occasions.
Michael C. Corballis, R. E. Traub
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Factor Analysis

2003
Wolfgang Härdle, Léopold Simar
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Risk factor analysis

Progress in Cardiovascular Diseases, 1984
William B. Kannel, Arthur Schatzkin
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