Weighing up degrees of freedom and variance?

#1
Just checking my thinking - if we had two models for 12 experimental cases.
Model 1 has 10 parameters, and accounts for 95% of variance
Model 2 has 2 parameters, and accounts for 90% of the variance

- If we replicated the study and predicted scores from each model, which model would be more accurate?

I think that model 2 will be more accurate as a predictor, Even though there is less variance accounted for, the model is simpler and therefore less constrained by losses of degrees of freedom and has less chance of a type 1 error due to a smaller amount of parameters.

Would you agree?
 

Dason

Ambassador to the humans
#2
It's impossible to say for sure. But yeah if you have 10 parameters for 12 observations then you're severely over fitting that model.