[R-sig-ME] compare fit of GLMM with different link/family

[Dries Debeer]

Dear,


I have a question about comparing the fit of GLMM with different link functions/families.

For instance, can the deviance or the AIC be used to compare the fit of probit and logit with the same parametrization?

probit_model <- glmer(Y ~ A + B + C*D + (A | subjects), data = data, family = binomial(link = "probit"))
logit_model <- glmer(Y ~ A + B + C*D + (A | subjects), data = data, family = binomial(link = "logit"))


And is this also possible when the distributional assumptions are different? For instance:

gamma_model <- glmer(X ~ A + B + C*D + (A | subjects), data = data, family = Gamma(link = "inverse"))
inverse_gauss <- glmer(X ~ A + B + C*D + (A | subjects), data = data, family = inverse.gaussian(link = "1/mu^2"))


Thank you!
Dries Debeer






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