I want to do univariate and multivariate binary logistic regression in SPSS. I am wondering about the timing of the Box-Tidwell test, is this both applicable to univariate and multivariate binary logistic regression? I am using a forward LR model, do I perform Box-Tidwell tests on all predictors that I placed in block 1 or just on the predictors that SPSS included in the forward LR model?
Moreover > what to do with a predictor if the linearity assumption is significant? Can I still include this predictor in the model in some way, or should I leave it out of the model?
It is better to apply Box-Tidwell test for Multivariate analysis. For detail please refere following:
https://www.youtube.com/watch?v=sciPFNcYqi8
Forget most of this and look at the attached references. Best wishes David Booth
Hello Michelle,
When you say, multivariate (binary) logistic regression, do you simply mean using a model with more than one independent variable/predictor? If so, it should more correctly be multivariable LR, as the usual definition of "multivariate" is inclusion of two or more dependent variables in a model.
The Box-Tidwell test may be applied if your model has one continuous IV, or if your model has multiple continuous IVs. I would assess it only for IVs that you elect to include in your final model. Whether IVs you don't intend to add to the model do or don't show the linearity. Do the check for all included continuous IVs.
Finally, I'm not a fan of automated variable inclusion (e.g., step methods, such as forward inclusion). There's a host of technical reasons underlying this, but one of the chief ones is, you are not guaranteed to identify the best ensemble of IVs for a given situation.
Good luck with your work.
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