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When to remove a non-significant predictor from a model?
When I remove this the AIC value goes up indicating the model without the significant variable is a worse fit. Should I remove the non-significant predictor or should I leave it in as it is a better model? Leave it in.
When to remove a non-significant variable from a regression?
I have run a multiple linear regression using stepwise regression to select the best model, however the best model returned has a non-significant variable. When I remove this the AIC value goes up indicating the model without the significant variable is a worse fit.
Is it safe to use stepwise variable selection?
NB: A corollary to Frank Harrell’s answer is that stepwise variable selection should not be used in the first place.
How did regression with nonstationary variables change in the early 1970s?
Chapter 4: Regression with Nonstationary Variables 57 changed in the early 1970s: a discrete rise in oil prices followed by OPEC’s waxing influ-ence, the move to floating exchange rates, the emergence of Japan as an industrial power and the increasing effects of globalization, and the entry of the baby-boom generation into
How can a regression be significant yet all predictors be non-significant?
Closed 8 years ago. How can a regression be significant yet all predictors be non-significant? If in a multiple linear regression (enter method) the general model isn’t significant (F>.05) but one of the predictors is significant (β<.05), should I consider it as a significant result?
How are predictors of multiple regression models dichotomous?
Both predictors are dichotomous (categorical). I have checked for multicollinearity. I am not sure if I have given enough info, but I cannot understand why predictor 1 has gone from being significant to non-significant and why the odds ratios are so different in the multiple regression model.
Is it a mistake to remove a non-significant variable?
That is, not only is it a mistake to discard that final ‘leftover’ non-significant covariate, but it was even more wrong to employ an automated procedure (stepwise variable selection) designed to produce a cascade of many such mistakes very quickly in an interdependent and irreproducible fashion.