https://communities.sas.com/t5/SAS-Procedures/Regression-with-interval-for-estimate/m-p/64615#M18355 There is a RESTRICT statement in PROC REG, but it doesn't allow "greater than" restrictions, just equality restrictions.<BR /> <BR /> The problem isn't really SAS. The problem is that when you perform a regression with multiple correlated variables (you have 7 variables in your model), least squares regression (not SAS) can have huge variances for your parameter estimates, and because of that, you can get a negative estimate even when you think it should be positive. In this situation, interpreting the coefficients is a meaningless exercise.<BR /> <BR /> Sometimes using Partial Least Squares regression (PROC PLS) can alleviate this problem, but your R-squared from PLS will not be as good as from PROC REG, and there's no guarantee that PLS will provide positive estimates. Wed, 11 May 2011 12:28:50 GMT Paige 2011-05-11T12:28:50Z https://communities.sas.com/t5/SAS-Procedures/Regression-with-interval-for-estimate/m-p/64614#M18354 Hi,<BR /> <BR /> This is the regression model i'm using:<BR /> <BR /> proc reg data=data_regressie4 outest=regressie4 edf;<BR /> BY ANALYS;<BR /> model geschaalde_FE = geschaalde_deviation age size total_experience firm_experience aantalsector aantalbedrijf;<BR /> run;<BR /> <BR /> The problem is that the estimate for geschaalde_deviation should be greater than 0. Is there a way to make sas estimate this model with "geschaalde_deviation" being greater than 0?<BR /> <BR /> Thanks a lot! Wed, 11 May 2011 11:58:43 GMT https://communities.sas.com/t5/SAS-Procedures/Regression-with-interval-for-estimate/m-p/64614#M18354 jebuske 2011-05-11T11:58:43Z https://communities.sas.com/t5/SAS-Procedures/Regression-with-interval-for-estimate/m-p/64615#M18355 There is a RESTRICT statement in PROC REG, but it doesn't allow "greater than" restrictions, just equality restrictions.<BR /> <BR /> The problem isn't really SAS. The problem is that when you perform a regression with multiple correlated variables (you have 7 variables in your model), least squares regression (not SAS) can have huge variances for your parameter estimates, and because of that, you can get a negative estimate even when you think it should be positive. In this situation, interpreting the coefficients is a meaningless exercise.<BR /> <BR /> Sometimes using Partial Least Squares regression (PROC PLS) can alleviate this problem, but your R-squared from PLS will not be as good as from PROC REG, and there's no guarantee that PLS will provide positive estimates. Wed, 11 May 2011 12:28:50 GMT https://communities.sas.com/t5/SAS-Procedures/Regression-with-interval-for-estimate/m-p/64615#M18355 Paige 2011-05-11T12:28:50Z