Help on negbink J. Hilbe 6-15-94 --------------- Log-link negative binomial regression Command line: ^negbink depvar predictors [if] [in] [=var], k(#) ^[lt] [it] [] o[] [] [] [] [] k(#) = value for alpha(k); default=1 (geometric regression) lt(#) = tolerance for convergence it(#) = number of iterations eform = results in exponential form (IRR ratio) o = offset variable nol = no display of iteration log nocon = noconstant model expec(#) = number of iterations using Fisher scoring (default=1) resid = creates the following variables: _mu (fit) _lp (linear predictor) _Pear (Pearson residual) _Dev (deviance residual) _SPear (standardized Pearson) _SDev (standardized deviance) _Hat (hat matrix diagonal) The value of alpha or k can be understood as the amount of overdispersion present in otherwise Poisson-type count data. Set k such that the value of the CHI2 dispersion following estimation approximates 1.0 For additional assistance contact by email: hilbe@@asu.edu