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Differences in error variance after HB estimation

Hi all,

I have a statistical question as well its application in Sawtooth. I have Best-Worst choice data, where people indicated a best and a worst option out of three alternatives. I estimated part-worth using Sawtooth HB CBC module for Best-Worst data. I guess the uniform prior is fine. A colleague is now concerned about differences in error variances and argue that me results highly depend on the error variance and that I can't compare different results (even within subject) as long as I do not control for it.
A friend suggested to use standardized variables (dependent and predictor variables). But I do have binary variables (dummy coded) only and the dependent is coded as 1, 0, or -1 (1: best, -1: worst). For me it doesn't make sense to standardize them and the estimation might not work if I have other than 1, 0, or -1 as input. Another way, suggested by a friend as well, is to to put a restriction such that variances in the var-cov matrix are identical (which is a strong assumption by the way). But I don't know how to do this.
Does anybody know how to deal with this issue? Every help is highly appreciated.

Best regards,
asked Feb 16, 2015 by tomic6126 (120 points)
retagged Mar 1, 2016 by Walter Williams

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