Using the Cement hardening data in Anderson (2008) Model Based Inference in the Life Sciences. A Primer on Evidence, and working with the best model which is lm ( y ~ x1 + x2, data = cement ) the AIC value from R is
model <- lm ( formula = y ~ x1 + x2 , data = cement ) AIC ( model ) 64.312 which can be converted to AICc by adding the bias correction factor 2*K*(K+1)/(n-K-1) to give the AICc value of 69.312 (addition of 5, where n=13 and K=4). This same value, 69.31, can be obtained using R package AICcmodavg library ( AICcmodavg ) data (cement) cement Cand.models <- list( ) Cand.models[[1]] <- lm ( y ~ x1 + x2, data = cement ) Cand.models[[2]] <- lm ( y ~ x3 + x4, data = cement ) Cand.models[[3]] <- lm ( y ~ x1 + x2 + x1 * x2, data = cement ) Cand.models[[4]] <- lm ( y ~ x3 + x4 + x3 * x4, data = cement ) ## vector of model names Modnames <- paste("MODEL", 1:4, sep=" ") ## AICc aictab ( cand.set = Cand.models, modnames = Modnames ) However, the AICc value reported by Anderson (2008) is 32.41. The AICc value obtained using RSS value (i.e., calculating AICc "manually" from the output of linear regression) is 32.41. Thanks for any help. David New R user, minimal familiarity with statistics. [[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.