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kjetil b halvorsen ♦
kjetil b halvorsen ♦
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I am running a binary logistic regression with 2 continuous predictors and their interaction. To test whether there is a linear relationship between the predictors and the logit of the dependent variable I have included an interaction term between the predictor and their associated natural logarithm. Unfortunately, for one predictor the interaction term is significant. This indicates to me that the assumption doesn't hold and that the inferences I am making are not valid.

How would you deal with such a scenario? Would you choose to transform the predictor and if so, how can I find an appropriate transformation? I have played around with a polynomial transformation. This did not solve the problem.

Beyond that, I would really like to avoid transformations of any sort to not complicate the interpretation that much.

Any advice is highly appreciated! Thanks much, Lukas

I am running a binary logistic regression with 2 continuous predictors and their interaction. To test whether there is a linear relationship between the predictors and the logit of the dependent variable I have included an interaction term between the predictor and their associated natural logarithm. Unfortunately, for one predictor the interaction term is significant. This indicates to me that the assumption doesn't hold and that the inferences I am making are not valid.

How would you deal with such a scenario? Would you choose to transform the predictor and if so, how can I find an appropriate transformation? I have played around with a polynomial transformation. This did not solve the problem.

Beyond that, I would really like to avoid transformations of any sort to not complicate the interpretation that much.

Any advice is highly appreciated! Thanks much, Lukas

I am running a binary logistic regression with 2 continuous predictors and their interaction. To test whether there is a linear relationship between the predictors and the logit of the dependent variable I have included an interaction term between the predictor and their associated natural logarithm. Unfortunately, for one predictor the interaction term is significant. This indicates to me that the assumption doesn't hold and that the inferences I am making are not valid.

How would you deal with such a scenario? Would you choose to transform the predictor and if so, how can I find an appropriate transformation? I have played around with a polynomial transformation. This did not solve the problem.

Beyond that, I would really like to avoid transformations of any sort to not complicate the interpretation that much.

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Lukas Preis
Lukas Preis

Correcting nonlinear relationship between continuous predictor and logit of dependent variable (Binary logistic regression)

I am running a binary logistic regression with 2 continuous predictors and their interaction. To test whether there is a linear relationship between the predictors and the logit of the dependent variable I have included an interaction term between the predictor and their associated natural logarithm. Unfortunately, for one predictor the interaction term is significant. This indicates to me that the assumption doesn't hold and that the inferences I am making are not valid.

How would you deal with such a scenario? Would you choose to transform the predictor and if so, how can I find an appropriate transformation? I have played around with a polynomial transformation. This did not solve the problem.

Beyond that, I would really like to avoid transformations of any sort to not complicate the interpretation that much.

Any advice is highly appreciated! Thanks much, Lukas