Testing a Simple Structure Hypothesis in Factor Analysis
PsychometrikaPublished 1 June 1966
K. G. Jöreskog
Citations157
SJR quartileQ1
SJR score1.90
SNIP2.06
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
It is assumed that the investigator has set up a simple structure hypothesis in the sense that he has specified the zero loadings of the factor matrix. The maximum-likelihood method is used to estimate the factor matrix and the factor correlation matrix directly without the use of rotation methods, and the likelihood-ratio technique is used to test the simple structure hypothesis. Numerical examples are presented.
Keywords
Computer Science
Journal of Business and Economic StatisticsAn Introduction to Multivariate Statistical Analysis
9,232 Citations1986Robb J. Muirhead, T. W. Anderson
BiometrikaA GENERAL DISTRIBUTION THEORY FOR A CLASS OF LIKELIHOOD CRITERIA
1,025 Citations1949George E. P. Box
Project Euclid (Cornell University)Statistical Inference in Factor Analysis
912 Citations1956T. W. Anderson, Herman Rubin
This paper discusses some methods of factor analysis and considers some mathematical problems of the model, such as whether certain kinds of observed data determine the model uniquely, and treats the statistical problems of estimation and tests of certain hypotheses.
PsychometrikaOn the Identifiability of Parameters in Thurstone's Multiple Factor Analysis
62 Citations1950Olav Reiersøl
The identifiability of parameters in four different factor analysis models is considered and the last of these four models corresponds to Thurstone's factor analysis.
British Journal of Statistical PsychologyESTIMATION IN FACTOR ANALYSIS UNDER VARIOUS INITIAL ASSUMPTIONS
32 Citations1958D. N. Lawley
Preprints of papers presented at the 14th national meeting of the Association for Computing Machinery on - ACM '59The method of resultant descents for the minimization of an arbitrary function
5 Citations1959R. W. Finkel
A method for minimization of algebraic and transcendental equations which is more rapidly convergent on nearly quadratic surfaces than the "steepest descents" methods described by Lance and entails significantly fewer computations than the method of "mixed descent" described by Guier.