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  • Object Scores in CATPCA

    From omalleypoker@hotmail.com@21:1/5 to All on Sat Jul 4 08:06:54 2020
    I've performed a CATPCA in SPSS and wish to use the components as explanatory variables in a logistic regression.

    I have finalised the CATPCA and am happy with the (5) principal components computed. However, when I attempt to extract the object scores to use in the regression model, I'm surprised to see that the values are either blank or zeros in each row.

    For reference, the 14 variables used in the CATPCA are a combination of nominal, numerical and ordinal. I've defined scales, discretized and, for missing data, defaulted to exclude (and impute a mode after for correlations after quantification).

    Can anybody shed some light on what, if anything, I'm doing wrong?

    Am I correct in interpreting object scores as component scores?

    Should I be extracting something else from the CATPCA to use in the logistic regression?

    Thanks in advance.

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  • From Rich Ulrich@21:1/5 to All on Sat Jul 4 18:00:35 2020
    On Sat, 4 Jul 2020 08:06:54 -0700 (PDT), omalleypoker@hotmail.com
    wrote:

    I will start by saying -
    [cribbed from an older message by Bruce]

    The SPSS mailing list (http://spssx-discussion.1045642.n5.nabble.com/)
    is a lot more active than this forum these days. You might want to
    join that list (if not already a member) and post your question there.
    Via the page given above, click on -more options- near the top for
    info on how to subscribe. HTH.


    I've performed a CATPCA in SPSS and wish to use the components
    as explanatory variables in a logistic regression.

    I have finalised the CATPCA and am happy with the (5) principal
    components computed. However, when I attempt to extract the
    object scores to use in the regression model, I'm surprised to see
    that the values are either blank or zeros in each row.

    That sounds like you should have a Warning or Error message.
    Or, all cases have been excluded because of Missing?


    For reference, the 14 variables used in the CATPCA are a combination
    of nominal, numerical and ordinal.

    Begging your pardon - I know nothing else about your data, and
    my own experience is not with CATPCA - but that sounds like a mess.

    In FA and PC, I've always wanted to have (a) one domain, or
    (b) a set of variables with "similar uniqueness" (if I may coin a
    phrase). Mixing nominal and scale does not seem promising for
    the goal of getting interpretable latent factors. - If they are not interpretable, what do you have?

    Is your N of cases at least 10 or 20 times the number of d.f. that
    you have for the 14 variables? - That will say something about
    how robust a solution is, but if there are more cases than d.f., it
    does not explain the absence of solution.

    I've defined scales, discretized and,
    for missing data, defaulted to exclude (and impute a mode after for >correlations after quantification).

    Can anybody shed some light on what, if anything, I'm doing wrong?

    Am I correct in interpreting object scores as component scores?

    Should I be extracting something else from the CATPCA to use in
    the logistic regression?


    --
    Rich Ulrich

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