##### Code for running an ANOVA in R


###Import data 


datum=read.csv(file.choose()) ### creates a data frame named datum from imported 
### csv file
head(datum) ### check data was imported properly

### Tell R that Protein is a categorical variable
### Same as 'Class' statement in SAS
datum$Protein=as.factor(datum$Protein) 


### Plot relationship
plot(Mass~Protein,data=datum) ### Generate a box and whiskers plot


### run an ANOVA using aov command


resultsAOV=aov(Mass~Protein,data=datum) ### run an ANOVA for effect of protein on mass,
### call the object 'results'
summary(resultsAOV) ### give summary of ANOVA
### returns anova table with SSE, MSE, F statistic and p-value
### Significant p-value indicates at least 2 groups are significantly different


### run an ANOVA using the lm command


results=lm(Mass~Protein,data=datum) ### run a regression with mass as dependent 
### and sex as independent variables
summary(results) ### Give results
### note F statistic from lm and aov give same results
### F statistics and p-values are at bottom of summary output


### Get confidence intervals on differrence between groups
confint(results)



### How to change the reference category


help(relevel) ###use the relevel command to change reference categories
results2=lm(Mass~relevel(Protein,ref="0.35"),data=datum) #Changes the reference group 
### to "0.35"
summary(results2)




### How to run a post-hoc analysis
TukeyHSD(results) 


##### Additional post-hoc tests - beyond scope of our class



### run a scheffe's comparison


library(agricolae) ### Scheffe's test is in the library (agricolae)
help(scheffe.test)
scheffe.test(resultsAOV,"Sex") ### run a scheffe's test