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I have two multiple linear regression models, built using the same groups of subjects, variables, the only difference is the time point: one is baseline data and the other is obtained some time after. I want to compare if there is any statistical significance between the two models. I have seen articles saying that using AIC maybe a better option over p-value when comparing models.

My question is: does it make sense to just purely compare the AIC using extractAIC in R, or to obtain the anova(lm)?

merv
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user1886016
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1 Answers1

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It is not standard to test for statistical significance between observations recorded at two points in time by estimating two different models.

You may mean that you are testing to see whether the observations recorded at a second point in time are statistically different from the first, by including some dummy variables, and testing the coefficients on these. Still, this is only estimating one model.

In your model you will have dummy variables for your second point in time, either one intercept or an intercept and an interaction dummy like this.

Then you should do both - test the p-value significance for either or both gammas in the models described, and also look at the AIC. There is no definitive 'better', as the articles likely described.

lilster
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