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Heteroskedasticity, extremity, and moderation in heterogeneous choice models


  • Garrett Glasgow

    () (University of California, Santa Barbara)


Heterogeneous choice models are extensions of binary and ordinal regression models that explicitly model the determinants of heteroskedasticity. I show that in many cases moderation (proximity to a choice threshold) will produce empirical results identical to heteroskedasticity in binary heterogeneous choice models, while extremity (a preference for endpoint categories) will produce empirical results identical to heteroskedasticity in ordinal heterogeneous choice models. I show how a simple extension of Williams' user-written oglm command (2006) can create heterogenous ordered choice models that can distinguish between heteroskedasticity, extremity, and moderation.

Suggested Citation

  • Garrett Glasgow, 2008. "Heteroskedasticity, extremity, and moderation in heterogeneous choice models," Fall North American Stata Users' Group Meetings 2008 16, Stata Users Group.
  • Handle: RePEc:boc:fsug08:16

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