search for: loc_cod

...#39;ve decided to include that in the final model. Positively skewed I'm thinking of doing a mixed effects model with random intercepts as the treatment code and zones within the treatment cose and random slopes as the seasons. mod2 <- lme(tthm ~ cl2free, random= ~ seasons| treatcode/loc_code) but that doesn't work. these seems to work good: mod2 <- lme(tthm ~ cl2free, random= ~ 1| loc_code, data=new.data, method="ML") mod3 <- lme(tthm ~ cl2free, random= ~ 1| treatcode/loc_code, data=new.data, method ="ML") mod2 has a lower AIC, so...

..., cex = 1.2, ylab = "Depth (m)", xlab = expression(Temperature~"("~degree*C~")"), scales = list( y=list(at=seq(0,120,20), limits = c(120,0), cex = 1.2), x=list(at=seq(3,18,3), alternating = c(2,1), limits = c(3,18), cex = 1.2))) Example data: EVENT, TRANSECT, LOC_CODE, TYPE, TEMP_C, Z_m 3 TC6 D MAX 15.6 1.2 3 TC6 D MEAN 14.8 1.1 3 TC6 D MIN 14.4 1.0 3 TC6 D POINT 11.3 55.8 3 TC6 D POINT 11.3 58.3 3 TC6 D POINT 11.3 58.3 3 TC6 D PROFILE 16.0 3.3 3 TC6 D PROFILE 16.0 3.2 3 TC6 D PROFILE 15.2 8.9 3 TC6 D PROFILE 12.6 14.8 3 TC6 D PROFILE 12.5 14.8...

...: int 10 5 1 1 6 1 1 8 23 7 ... $ suburb : chr "WARBURTON COMMUNITY" "WESTMINSTER" "WESTMINSTER" "WESTMINSTER" ... $ postcode : int 6431 6061 6061 6061 6150 6160 6160 6160 6016 6016 ... $ state : int 5 5 5 5 5 5 5 5 5 5 ... $ loc_code : chr "E06001" "" "" "" ... $ lga : int NA NA NA NA NA NA NA NA NA NA ... $ dob_my : num 1.27e+12 1.27e+12 1.27e+12 1.27e+12 1.27e+12 ... $ dob_ddmwdob : int 0 0 0 0 0 0 0 0 0 0 ... $ age : int 0 0 1 2 0 0...