>>>>> "JohnF" == John Fox <[EMAIL PROTECTED]> >>>>> on Sat, 27 Nov 2004 23:49:08 -0500 writes:
JohnF> Dear Seth, JohnF> You don't say which variable is the explanatory JohnF> variable and which is the response, but assuming that JohnF> prob is to be regressed on effect, you can fit JohnF> lm(prob - 50 ~ I(effect + 37.25) - 1). That is you JohnF> can shift the point through which the regression is JohnF> to go to the origin and then force the regression JohnF> through the origin. JohnF> I hope this helps, yes, nice! Even a bit more useful {though slightly uglier} is to use offset(): mfit <- lm(prob ~ offset(50+ 0*effect) + I(effect + 37.25) - 1) such that e.g. predict(mfit, ...) will still predict 'prob' Note however that for both solutions, the regression abline() will look wrong {and I hoped it would also be ok when using offset()}, plot(prob ~ effect) ; abline(mfit) Martin JohnF> John JohnF> -------------------------------- JohnF> John Fox JohnF> Department of Sociology JohnF> McMaster University JohnF> Hamilton, Ontario JohnF> Canada L8S 4M4 JohnF> 905-525-9140x23604 JohnF> http://socserv.mcmaster.ca/jfox JohnF> -------------------------------- >> -----Original Message----- >> To: [EMAIL PROTECTED] >> Subject: [R] lm help: using lm when one point is known (not y intercept) >> >> Hello- >> >> My question is a short one. How can I specify a single point >> which through the fitted linear model has to go through? To >> illustrate my problem, the fit to following data must go >> through the point (-37.25(effect), 50(prob)). Note: you can >> ignore the label column. >> >> Effect Prob Label >> >> 1 -1143.75 7.142857 L >> 2 -572.75 21.428571 D >> 3 -223.75 35.714286 GL >> 4 123.25 50.000000 DG >> 5 359.75 64.285714 G >> 6 374.75 78.571429 DGL >> 7 821.75 92.857143 DL >> >> Thanks in advance! >> >> Seth Imhoff ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html