# Sawtooth latent class gives T ratio and standard errors, what to do with it? how check for significance?

Hello,

I am doing my conjoint analysis with Sawtooth Latent Class. I want to check whether the attribute(levels) and interactions I added, are significant. I clicked the checkbox report standard errors and I got next to my attribute levells' utilities, the t ratio's and the standard errors. But what should I now do with it? How do I check with these t ratio's and st. errors whether my levels and interactions are significant?
I hope you can help me.

Thanks in advance
asked May 3, 2012
retagged Sep 13, 2012

## 1 Answer

0 votes
What typically one would do would be to look at the fit statistics overall for the Latent Class run.  You will get a Log-Likelihood for the Latent Class model.  You can compare the LL for the latent class models with main effects only vs. the LL for the result when you include interactions.  (Make sure to keep the number of classes constant between the models).

I may be wrong here, but the statistical test would involve counting the number of parameters added to the model times the number of segments in your LC solultion (somebody please correct me if I'm wrong).

So, if you were adding a 2-way interaction between an attribute with 5 levels and another with 4, there would be an additional (5-1)(4-1)=12 parameters to the model.   But, since we have three groups, I think it means there are actually 12*3 = 36 degrees of freedom for our statistical test (the 2-LL test).

So, if you saw a difference in LL of 10 points between the model with and without interactions, then the Chi-square test involves a critical value of 10x2 = 20 with 36 degrees of freedom.  Use the =ChiDist(20,36) formula in Excel to compute the p-value.  A p-value of 0.05 or less would indicate that the interaction effect was adding significant fit.
answered May 3, 2012 by Platinum (162,590 points)