In econometrics economic theory often predicts a particular sign for a slope variable. One often gets wrong signs on variables but the coefficients as estimated, in such cases are usually both statistically and economically insignificant. In such cases one generally re-estimates the equation with the variable omitted (imposing a zero sign. Perhaps re-estimating with the variable missing is the simplest solution. Of course, I agree that if the variable is significant and of the wrong sign there is something wrong with the theory or the data.
John On 1 June 2011 03:40, Rolf Turner <rolf.tur...@xtra.co.nz> wrote: > > (1) You can easily force the slope to take on a *particular* value, > positive or negative, by using offset(). However just to constrain > the value of the slope to be less than or equal to 0 you'd have to > do a constrained optimization of the sum of squares. Not hard to > do, but probably (almost surely) unwise. If the data are telling you > that the slope is positive, don't argue with them. > > Also if you constrain slope <= 0 and the data want the slope > to be greater than 0, then the constrained optimum will probably > be at slope == 0. > > If you want it to be *less* than 0, you'd have to constrain it with > slope <= - epsilon for some (positive) epsilon. And then I'd guess > you'd wind up with a slope of -epsilon. So you might as well fix > the slope at -epsilon and use offset(). > > But the whole idea makes no sense. So: The executive > summary is ``Don't do it.'' > > (2) Your example data don't make any sense either. You > present the values of only one variable. For a regression you > need to have a y-variable and at least one x-variable. It would > appear that you're not thinking very clearly. > > cheers, > > Rolf Turner > > On 01/06/11 11:32, J S wrote: >> >> Dear forum members, >> >> >> >> How can I force a negative slope in a linear regression even though the >> slope might be positive? >> >> >> >> I will need it for the purpose of determining the trend due reasons other >> than biological because the biological (genetic) trend is not positive for >> these data. >> >> >> >> Thanks. Julia >> >> >> >> >> Example of the data: >> >> >> >> [1] 1.254 1.235 1.261 0.952 1.202 1.152 0.801 0.424 0.330 0.251 0.229 >> 0.246 >> >> [13] 0.414 0.494 0.578 0.628 0.514 0.594 0.827 0.812 0.629 0.928 0.707 >> 0.976 >> >> [25] 1.099 1.039 1.272 1.398 1.926 1.987 2.132 1.644 2.174 2.453 2.392 >> 3.002 >> >> [37] 3.352 2.410 2.206 2.692 2.653 1.604 2.536 3.070 3.137 4.187 4.803 >> 4.575 >> >> [49] 4.580 3.779 4.201 5.685 4.915 5.929 5.474 6.140 5.182 5.524 5.848 >> 5.830 >> >> [61] 5.800 7.517 6.422 >> >> [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- John C Frain Economics Department Trinity College Dublin Dublin 2 Ireland www.tcd.ie/Economics/staff/frainj/home.html mailto:fra...@tcd.ie mailto:fra...@gmail.com ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
