setwd("C:/Documents and Settings/William Christensen/My Documents/stat230") ################################################# ### AUDITOR TRAINING (Randomize Complete Block CB[1]) ### ################################################# ## Either of the two lines below will access the data ## audit <- read.table("auditor.csv", sep=",", header=TRUE) audit <- read.table(header=TRUE, text=" score block method 73 1 home 81 1 local 92 1 national 76 2 home 78 2 local 89 2 national 75 3 home 76 3 local 87 3 national 74 4 home 77 4 local 90 4 national 76 5 home 71 5 local 88 5 national 73 6 home 75 6 local 86 6 national 68 7 home 72 7 local 88 7 national 64 8 home 74 8 local 82 8 national 65 9 home 73 9 local 81 9 national 62 10 home 69 10 local 78 10 national ") audit audit$block <- factor(audit$block) audit$method <- factor(audit$method) audit.lm <- lm(score ~ block + method , data=audit) tapply(audit$score, audit$method, mean) anova(audit.lm) ################################################# ### DENTAL PAIN (CB[2]) ### ################################################# dental <- read.table(header=TRUE, text=" relief block codeine acupunc 0.0 1 1 1 0.6 1 1 2 0.5 1 2 1 1.2 1 2 2 0.3 2 1 1 0.7 2 1 2 0.6 2 2 1 1.3 2 2 2 0.4 3 1 1 0.8 3 1 2 0.8 3 2 1 1.6 3 2 2 0.4 4 1 1 0.9 4 1 2 0.7 4 2 1 1.5 4 2 2 0.6 5 1 1 1.5 5 1 2 1.0 5 2 1 1.9 5 2 2 0.9 6 1 1 1.6 6 1 2 1.4 6 2 1 2.3 6 2 2 1.0 7 1 1 1.7 7 1 2 1.8 7 2 1 2.1 7 2 2 1.2 8 1 1 1.6 8 1 2 1.7 8 2 1 2.4 8 2 2") dental$block <- factor(dental$block) dental$codeine <- factor(dental$codeine) dental$acupunc <- factor(dental$acupunc) dental.lm <- lm(relief ~ block + codeine + acupunc + codeine:acupunc, data=dental) tapply(dental$relief, dental$codeine, mean) tapply(dental$relief, dental$acupunc, mean) tapply(dental$relief, dental$codeine:dental$acupunc, mean) anova(dental.lm) #### TYPE I AND TYPE III ANOVA TABLES ###### object <- read.csv("filename", header = TRUE, sep = ",") head(object) library(car) #If this isn't working for you, then you need to install the car package # ANOVA with Type I SS model <- lm(response ~ factor1 + factor2 + factor1 * factor2, data = object) anova(model) # ANOVA with Type III SS model2 <- lm(response ~ factor1 + factor2 + factor1 * factor2, data = object, contrasts = list(factor1 = contr.sum, factor2 = contr.sum)) #Don't worry too much about understnding this "contrast" statement Anova(model2, type = "III") #Don't need to include the Intercept line of the ANOVA table