Hi, This is a fairly naive question:  I am trying to create a regression model for somewhat skewed and clustered survey data.  A professor suggested I use maximum likelihood estimation with GLS, rather than OLS, to account for some of the heteroskedasticity and autocorrelation in my data.  As far as I am aware, PROC REG uses OLS, PROC GLM uses ML, and PROC MIXED uses REML.  However, these methods (see code below) all seem to yield the same estimates.  Why is this?  Shouldn't changing the estimation method change my estimates and standard errors? proc reg;   Model y= x1 x2 x3 x4 x5;   weight weights;   run; proc glm;   Model y= x1 x2 x3 x4 x5 /solution;   weight weights;   run; proc mixed Method=REML;   Model y= x1 x2 x3 x4 x5 /solution;   weight weights;   run; ... View more