On Nov 08, 2011 at 11:16am Colin Aitken wrote: > An unresolved problem is: what does R do when the explanatory factors > are not defined as factors when it obtains a different value for the > intercept but the correct value for the fitted value?
Colin, I don't think that happens (that the fitted values are identical if predictors are cast as numerical), but the following could (really is answered by my initial answer). Once again, using the example I gave above, but using the second level of "outcome" as a reference level for a new fit, called glm.D93R. (For this part of the question a corpse would have been nice, though not really needed---"yours" was unfortunately buried too deeply for me to find it,) ## Dobson (1990) Page 93: Randomized Controlled Trial : counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9) treatment <- gl(3,3) glm.D93 <- glm(counts ~ outcome + treatment, family=poisson()) glm.D93R <- glm(counts ~ C(outcome, base=2) + treatment, family=poisson()) ## treat predictor as numeric glm.D93N <- glm(counts ~ as.numeric(as.character(outcome)) + as.numeric(as.character (treatment)), family=poisson()) > coef(glm.D93) (Intercept) outcome2 outcome3 treatment2 treatment3 3.044522e+00 -4.542553e-01 -2.929871e-01 1.337909e-15 1.421085e-15 ## Different value for the Intercept but same fitted values (see below) as the earlier fit (above) ## summary(glm.D93R) < snipped and edited for clarity> Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 2.590e+00 1.958e-01 13.230 <2e-16 *** outcome1 4.543e-01 2.022e-01 2.247 0.0246 * outcome3 1.613e-01 2.151e-01 0.750 0.4535 treatment2 -3.349e-16 2.000e-01 0.000 1.0000 treatment3 -6.217e-16 2.000e-01 0.000 1.0000 < snip > > fitted(glm.D93) 1 2 3 4 5 6 7 8 9 21.00000 13.33333 15.66667 21.00000 13.33333 15.66667 21.00000 13.33333 15.66667 > fitted(glm.D93R) 1 2 3 4 5 6 7 8 9 21.00000 13.33333 15.66667 21.00000 13.33333 15.66667 21.00000 13.33333 15.66667 ## if predictors treated as numeric---check summary(glm.D93N) yourself > fitted(glm.D93N) 1 2 3 4 5 6 7 8 9 19.40460 16.52414 14.07126 19.40460 16.52414 14.07126 19.40460 16.52414 14.07126 Regards, Mark. ----- Mark Difford (Ph.D.) Research Associate Botany Department Nelson Mandela Metropolitan University Port Elizabeth, South Africa -- View this message in context: http://r.789695.n4.nabble.com/Estimate-of-intercept-in-loglinear-model-tp4009905p4017091.html Sent from the R help mailing list archive at Nabble.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.