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Presentation transcript:

Mar-16H.S.1Mar-16H.S.1 Stata 5, Mixed Models Not finished Hein Stigum Presentation, data and programs at:

Mar-16H.S.2 Dependent data Ability to recognize neighbor car

Mar-16H.S.3 Distribution by sex

Mar-16H.S.4 Model 1 regress rcModel without sex predict res, resResiduals twoway (scatter res id)Residual plot

Mar-16H.S.5 Residuals sorted

Mar-16H.S.6 Model 2 gen male =(sex==0) gen female=(sex==1) regress rc male female, noconstModel with sex predict res, resResiduals twoway (scatter res id)Residual plot Model results: male = 0.7 female=-0.7

Mar-16H.S.7 3 lessons learned 1.Omitting predictor  dependent residuals 2.Not evident from residual plot 3.+ constant terms  remove dependencies 4.y-data may be dependent, y|x (or residuals) must be independent

Mar-16H.S.8 2 data sets

Compare regression methods Fixed effects models Conditional models Mixed models Mar-16H.S.9