Saturday, April 01, 2017

AMOS, you can't get the usual fit indices with missing data

  • Many fit indices are only defined for the complete data case
  • Computing the chi square statistic requires fitting the saturated model. When some data values are missing, Amos 3.6 does not do this because it is time consuming. With complete data, it takes practically no time at all. Most other fit measures depend on the chi square statistic, and so they are not reported either. Also, as you noted, modification indices are not reported. Besides the various fit measures that depend on chi-square, and the modification indices, there is no other output that is unavailable with missing data.
  • If you have missing data, CMIN is a "Function of the log-likelihood," and not a chi-square statistic. If you have several nested models, you can construct LR chi-square statistics from the respective CMIN values.
  • The "Function of the log-likelihood" does not come with a p-value.

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