I?m confused by the difference in the fit of a gam model (in package mgcv) when I specify an interaction in different ways. I would appreciate it if someone could explain the cause of these differences. For example: x <- c(105, 124, 124, 124, 144, 144, 150, 176, 178, 178, 206, 206, 212, 215, 215, 227, 229, 229, 229, 234, 234, 254, 254, 290, 290, 303, 334, 334, 334, 344, 345, 345) y <- c(0.31, 1.41, 2.87, 1.92, 0.31, 0.31, 0.31, 0.31, 0.31, 0.31, 0.31, 0.31, 0.31, 1.92, 0.31, 0.31, 0.31, 0.31, 0.31, 0.31, 0.31, 2.08, 2.28, 1.59, 2.13, 2.77, 3.97, 4.54, 4.35, 3.6, 5.2, 4.6) loc <- c("S", "N", "S", "S", "N", "N", "S", "S", "N", "N", "N", "N", "S", "N", "S", "S", "N", "S", "S", "N", "N", "N", "N", "N", "N", "S", "N", "S", "S", "N", "S", "S") locf <- as.factor(loc) locN <- as.numeric(loc=="N") locS <- as.numeric(loc=="S") # fit the model with a separate smooth for loc = N and loc = S fit1 <- gam(y ~ locf + s(x, by=locN) + s(x, by=locS)) # fit the model with a separate smooth for each level of the factor loc (N and S) fit2 <- gam(y ~ locf + s(x, by=locf)) # The shape of the relations are similar, but the vertical locations are different, # and the size of the standard errors of the smooth are different windows() par(mfrow=c(2, 2), mar=c(4, 4, 2, 1)) plot(fit1) plot(fit2) # The R-sq., deviance explained, GCV score, and scale est. are the same, # but the estimates and degrees of freedom are different summary(fit1) summary(fit2) I'm using R version 2.13.0 (2011-04-13) and mgcv version 1.7-6 on Windows XP. Thanks for your help. Jean `·.,, ><(((º> `·.,, ><(((º> `·.,, ><(((º> Jean V. Adams Statistician U.S. Geological Survey Great Lakes Science Center 223 East Steinfest Road Antigo, WI 54409 USA http://www.glsc.usgs.gov (GLSC web site) jvadams@usgs.gov (E-mail) [[alternative HTML version deleted]]