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A MONTE CARLO AID TO THE EVALUATION OF MAXIMUM LIKELIHOOD FACTOR ANALYSIS SOLUTIONS
Author(s) -
Heeler Roger M.,
Whipple Thomas W.
Publication year - 1976
Publication title -
british journal of mathematical and statistical psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.157
H-Index - 51
eISSN - 2044-8317
pISSN - 0007-1102
DOI - 10.1111/j.2044-8317.1976.tb00717.x
Subject(s) - monte carlo method , maximum likelihood , factor (programming language) , mathematics , statistics , restricted maximum likelihood , hybrid monte carlo , random effects model , statistical physics , computer science , markov chain monte carlo , physics , medicine , meta analysis , programming language
Monte Carlo determined factor structures are used to derive the basic random level of fit when restricted maximum likelihood factor analysis is used to evaluate the fit of a particular hypothetical model. The performance of the hypothesized model is then assessed in relation to the maximal fit obtainable and the basic random level of fit.