Re: Big odds ration in binary regression output

Posted by Art Kendall on Aug 24, 2017; 11:30am
URL: http://spssx-discussion.165.s1.nabble.com/Big-odds-ratio-in-binary-regression-output-tp5734731p5734757.html

perhaps you should go back to the factor analysis.

How did you decide how many factors to retain?
Did you do a parallel analysis? (See the archives for macros to do this).

Did you use principal factors so you used only the common variance?

Did you use varimax rotation to maximize divergent validity?

In developing the scoring key did you reflect items with negative (possibly positive) loadings so all repeated measures of the construct were pointing in the same direction?
Did you drop items that did not load cleanly?

I suggest you use unit weights, i.e., simply take the mean of the clean loading items so the resulting scale is on the same metric as the item response scale. (Following this conventional approach facilitates using the scales in future research by yourself and others. (Non-unit weights rarely stand up across studies.)

When you redo your analysis try using the scale scores without coarsening to see the results.  Then coarsen the scales to see if results are robust enough to withstand the coarsening of measurement.