In article <912u8q$eti$[EMAIL PROTECTED]>,
John Uebersax <[EMAIL PROTECTED]> wrote:
>I think all the comments supplied by other posters are relevant.
>Of course you should check to make sure that SAS is reading the input
>matrix correctly, as was pointed out. However, even assuming that you
>did everything correctly I'm not surprised that SAS has a problem
>factoring the matrix. A correlation matrix composed of tetrachorics
>may not be factorable--especially if there is a large number of items.
>That can be remedied by "conditioning" the matrix. For a discussion,
>see the paper by Knol and Berger (the Parry & McArdle paper might also
>talk about this):
>Knol DL, Berger MP. Empirical comparison between factor analysis and
>multidimensional item response models. Multivariate Behavioral
>Research, 1991, 46, 457-477.
>Parry CD, McArdle JJ. An applied comparison of methods for least-
>squares factor analysis of dichotomous variables. Applied Psychological
>Measurement, 1991, 15, 35-46.
>Note that conditioning the matrix in this way is a completely "ad hoc"
>procedure.
If one wishes to adopt the tetrachoric model, what really
should be done is to use the likelihood function for the
entire sample based on the assumption that there is an
underlying multivariate normal distribution, and that the
observations are obtained by dichotomizing the variables.
This would not use any of the bivariate tetrachoric
computations, and would produce a legitimate model.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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