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1

Model selection criteria, such as the BIC, the AIC, or the minimum length criterion, are commonly used in the literature, so nobody would laugh and point at you if you use them (and if they do, please reconsider your acquaintance). However, the validity of these criteria rely on some strong assumptions, that you will need to verify and justify. For instance, ...


0

I can only agree on the issue with tiny differences as this example states. In general, what I can say from my personal experience (mainly academic), BIC differences can be be treated according to the following boundaries: If the absolute difference $\delta$ is greater 10, the smaller BIC value is considerable better. $\mid BIC_1-BIC_2\mid > 10$ If the ...


3

It's certainly possible to have a situation in which only the interaction is significant. A trivial example is: > set.seed(12) > x1 <- rnorm(100,0,1) > x2 <- rnorm(100,0,1) > cor(x1,x2) [1] 0.01592198 > y <- x1*x2 + rnorm(100,0,.3) > modFull <- lm(y~x1+x2+x1:x2) > modIntOnly <- lm(y~x1:x2) > anova(modIntOnly,modFull) ...


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