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DETECTION OF CORRELATED ERRORS IN LONGITUDINAL DATA
Author(s) -
Sörbom Dag
Publication year - 1975
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.2044-8317.1975.tb00558.x
Subject(s) - variance (accounting) , statistics , measure (data warehouse) , mathematics , econometrics , maximum likelihood , computer science , data mining , accounting , business
A study of change in ability between two occasions may employ a number of tests believed to measure the ability in question. Either the same battery of tests is used on both occasions, or equivalent forms are used. For a variety of reasons, correlations may exist between certain errors remaining after eliminating variance due to true scores, and hence the classical factor analysis model is not applicable. A procedure for detecting correlations between errors is discussed. A search strategy is proposed since, even if the number of observed variables is small, the number of possible models is very large. A computer program is described, which produces maximum‐likelihood estimates for the parameters in a factor analytic model in which the error variables may be correlated.