# READ A STRUCTURED DATA TABLE K=read.table("c:/2008LinearModelsData/bankR.txt") K # ASSIGNING VARIABLES X=K$deposit Y=K$newacc B=factor(K$bin) # FINDING N & C n=length(X) n c=nlevels(B) c # ANOVA OF FITTED MODELS anova(lm(Y~B)) #FULL MODEL anova(lm(Y~X)) #REDUCED MODEL # CALCULATING SUM OF SQUARES ERROR # FOR FULL MODEL MF=summary(lm(Y~B),digits=10) MSEF=MF$sigma^2 dfF=MF$df[2] SSEF=dfF*MSEF SSEF # CALCULATING SUM OF SQUARES ERROR # FOR REDUCED MODEL MR=summary(lm(Y~X),digits=10) MSER=MR$sigma^2 dfR=MR$df[2] SSER=dfR*MSER SSER # CALCULATING GLM F STATISTIC F=((SSER-SSEF)/(dfR-dfF))/(SSEF/dfF) F # FINDING CRITICAL VALUE alpha=0.01 CV=qf(1-alpha,c-2,n-c) CV # PROBABILITY VALUE P=1-pf(F,c-2,n-c) P # THE EFFICIENT WAY TO DO THIS # SPECIFY FULL VS REDUCED MODELS: FM=lm(Y~B) RM=lm(Y~X) # CALCULATE ANOVA TABLE OF COMPARISON anova(RM,FM)