Compare Fit of two linear models

Hi guys,

I have a model that looks like this (DV ~ IV1 + IV2)

I also have a nested model where I constrained the coefficients of IV1 and IV2 to be equal. Is there a function I can use to compare the model fit of these two models?

(so I can see if the fit get significantly worse or not in the nested model).

In R I would use CompareFit from the lavaan package, is there something similar for Matlab?

Thanks in advance.

Answer 1

[Jeff Miller]

A quick and dirty solution is to form a new variable

S=IV1+IV2;

and then compare the fit of the model 'DV~S' to the model 'DV~S+IV2'. If the second model fits significantly better, then you know the constrained model with equal slopes is significantly worse.

[Femke R]

I've found how to constrain them, I just need to know if there's a way to compare model fit (with significance). To see if the drop in fit is actually significant.

[Jeff Miller]

X = [S,IV2];
mdl = fitlm(X,DV)

Under the mdl.Coefficients output, you will see a pValue for X2. If this is less than .05 (or whatever your alpha is), then the drop is statistically significant.