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I would like to test the effects of salinity and temperature on parasite infection. Temperature and salinity are the fixed factors, the first one has two levels, the second one three levels. Individual identity nested with waterbath are my random factors. So the treatments in total are 6 (salinity1*temperature1, salinity2*temperature1, salinity3*temperature1, salinity1*temperature2, salinity2*temperature2, salinity3*temperature2), with 12 replicates (mussels host) for each treatment.

I'm analysing the dataset using GLMM negative binomial or poisson family. For testing the best model, since the sample size is 12 in each treatment, should I choose the AIC corrected for small sample size (from the library MuMin) instead of the normal AIC?

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