data <- matrix(scan(),ncol=2,byrow=TRUE) 1 1 1 2 1 3 2 3 2 4 2 5 3 5 3 6 3 7 data GLMexample1 <- data.frame(data) colnames(GLMexample1) <- c("group","y") GLMexample1$group <- as.factor(GLMexample1$group) # to make sure that group is a factor, not numeric rm(data) GLMexample1$x1 <- (GLMexample1$group == "1")*1 # creating dummy variables for the regression model GLMexample1$x2 <- (GLMexample1$group == "2")*1 options(contrasts = c("contr.SAS","contr.poly")) # set dummy coding to match the scheme in SAS summary(lm(y ~ group, data = GLMexample1)) anova(lm(y ~ group, data = GLMexample1)) summary(lm(y ~ x1 + x2, data = GLMexample1)) anova(lm(y ~ x1 + x2, data = GLMexample1)) rm(GLMexample1) # clean up when we are done