mnrfit : how to include interaction terms ?

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laurie on 20 Aug 2013
I would like to compute a logistic regression on accuracy data (accuracy is 0 or 1).
There are 3 predictors (X1, X2, X3) of accuracy, but i would like to include the interaction terms between those predictors (X1*X2,..., X1*X2*X3) in the model.
How can I achieve this ? I can't figure out how to set up B or parameter values to achieve this. Any ideas ? Should I switch to another function (for example, compute log-likelihood ratios separately then run regstats/regress or something else on them) ? Thanks a lot.
laurie on 21 Aug 2013
similarly, how to set this up so that one predictor is taken in as a random effect ? :-/

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Accepted Answer

the cyclist
the cyclist on 21 Aug 2013
I think you may need to use nlinfit() or nlmefit() to do what you need.
laurie on 21 Aug 2013
thanks ! just found the example you wrote on the forum.
this might be a stupid idea, but what if i was to compute the log likelihood of a correct answer for each predictor combination for each subject, then run a simple stepwise regression ? would that be appropriate ? i gather the only non linear part in logistic regression is in WHAT is fitted (that has to be transformed using the logit formula), not in how it is fitted (the relationship between the predictors and the logit data is actually linear) right ?

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