Contents
What should a regression model include?
When building a linear or logistic regression model, you should consider including:
- Variables that are already proven in the literature to be related to the outcome.
- Variables that can either be considered the cause of the exposure, the outcome, or both.
- Interaction terms of variables that have large main effects.
Why include more variables in regression?
Adding more terms to the multiple regression inherently improves the fit. It gives a new term for the model to use to fit the data, and a new coefficient that it can vary to force a better fit. Adding more and more variables makes it more and more likely that you will overfit your model to the training data.
Can a matched sample be analysed using regression?
If you manually matched, used psmatch2in Stata, or used MatchItin R, then effects are typically estimated using regression in the matched set, optionally including covariates in the regression. Austin, P. C., & Small, D. S. (2014).
What should be included in a regression model?
When building a linear or logistic regression model, you should consider including: 1 Variables that are already proven in the literature to be related to the outcome 2 Variables that can either be considered the cause of the exposure, the outcome, or both 3 Interaction terms of variables that have large main effects
Is the set of choices in matching the same as regression?
My intuition is that set of choices in matching is strictly a subset of regression. 1-to-1, k-to-1 has a regression equivalent: Dropping outliers, influential observations, or, conversely, extrapolation, etc.. Yet regression adds choices re functional form restrictions for the outcome equation that are not available in pure matching.
Is it possible to do matching without regression?
Matching is a way to discard some data so that the regression model can fit better. Trying to do matching without regression is a fool’s errand or a mug’s game or whatever you want to call it. Jennifer and I discuss this in chapter 10 of our book, also it’s in Don Rubin’s PhD thesis from 1970!