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SPSS identification restrictions on EFA models

Discussion in 'Education' started by D. Bontempo, Oct 8, 2018.

  1. D. Bontempo

    D. Bontempo Guest

    I am trying to understand the restrictions used by SPSS to identify EFA models using ML extraction. FOr example the GFI for a 2 factor model of 8 items (shown below) has 13df

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    I understand to identify EFA models m-squared restrictions are needed, where m=#of factors. I have also seen the formula [(p−m)2−(p+m)]/2 for the df of the chi-sq test.

    This 2-factor model of 8 items needs 2^2=4 restrictions. We get 3 from fixing the factor var-covar matrix to 1 for factors and 0 for factor covarience.

    How is the additional restriction obtained? 13 df mean one loading appears to be fixed to zero, or some restriction has been placed on a function of loadings. But the unrotated solution has 24 loadings reported, none of which are 0.

    Even a text discussing how to restrict this model for estimation would be appreciated.

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