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From |
rgutierrez@stata.com (Roberto G. Gutierrez, StataCorp) |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: How to model heterogeneity in level 1 residual variance (sigma^2)? |

Date |
Thu, 20 Mar 2008 10:52:57 -0500 |

HsienYuan Hsu <hsuhy0914@gmail.com> writes: > I am tring to model heterogeneity in level 1 residual variance (sigma^2). > In my model, I have > DV: mathach > IV: Female > If I use the syntax: > xtmixed mathach female || id:female , cov(unstruct) nocons , ml > It gives me "one sigma^2. However, I want to model the sigma^2 for male and > female, respectively. Does any expert know the syntax? Modeling observation-level heterogeneity requires first creating a variable identifying the observations and then explicitly adding this level to the model . gen obs = _n . xtmixed mathach female || id:female, cov(unstruct) nocons /// || obs:female, nocons ml variance When you fit this model, the variance component for the "obs" level represents the added variability due to being female at the residual level. Mathematically, sigma^2 for males is var(Residual) as labeled in the output; sigma^2 for females is var(Residual) + var(female), for var(female) as given in the "obs:" level of the model. If this model does not converge, it is most likely because there is no added variability due to being female -- sigma^2 for females is actually less than that for males. No problem -- simply reverse the coding . gen male = 1 - female . xtmixed mathach female || id:female, cov(unstruct) nocons /// || obs:male, nocons ml variance and now sigma^2 for females is var(Residual) and that for males is var(Residual) + var(male). --Bobby rgutierrez@stata.com * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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