################## long format
mydataframe <- read.delim ("http://www.robin-beaumont.co.uk/virtualclassroom/book2data/ttest_2independent_long1.txt", header=TRUE)
### local copy ignore:
# mydataframe <- read.delim("D:\\web_sites_mine\\HIcourseweb 
# new\\book2data\\ttest_2independent_long1.txt", header=TRUE)
###
names(mydataframe)
length(mydataframe)

t.test (values ~ ind, var.equal=TRUE, data=mydataframe, conf.level=.95)

#from R Commander:
numSummary(mydataframe[,"values"], groups=mydataframe$ind, 
  statistics=c("mean", "sd", "IQR", "quantiles"), quantiles=c(0,.25,.5,.75,1))
plotMeans(mydataframe$values, mydataframe$ind, error.bars="conf.int", 
  level=0.95)
# above manually anotated to cnage y axis scale to match boxplot;
plotMeans(mydataframe$values, mydataframe$ind, error.bars="conf.int", 
  level=0.95, ylim=c(0,600))     
 # R Commander uses the Boxplot function in the car package
# this provides the  id.method option. 
Boxplot(values~ind, data=mydataframe, id.method="y")

# Manual changes:
Boxplot(values~ind, data=mydataframe, id.method="y")# show extremes + case numbers
Boxplot(values~ind, data=mydataframe, id.method="n")# show extremes NO case numbers
Boxplot(values~ind, data=mydataframe, id.method="identify") #interactive identification

################## wide format
 mydataframe <- read.delim ("http://www.robin-beaumont.co.uk/virtualclassroom/book2data/ttest_2independent_wide1.txt", header=TRUE)
### local copy ignore:
# mydataframe <- read.delim("D:\\web_sites_mine\\HIcourseweb 
# new\\book2data\\ttest_2independent_wide1.txt", header=TRUE)
#### 
names(mydataframe)

t.test  (mydataframe$treatment, mydataframe$control, var.equal=TRUE, conf.level=.95)
# effect size
effectsize <- (mean(mydataframe$treatment) - mean(mydataframe$control))/sapply(stack(mydataframe), sd)
effectsize
################ long again
 mydataframe2 <- read.delim("http://www.robin-beaumont.co.uk/virtualclassroom/book2data/ttest_2independent_long1.txt", header=TRUE)

### local copy ignore
# mydataframe2 <- read.delim("D:\\web_sites_mine\\HIcourseweb 
# new\\book2data\\ttest_2independent_long1.txt", header=TRUE)
###

names(mydataframe2)
t.test (values ~ ind, var.equal=TRUE, data=mydataframe2)

# Base package functions:
# stack and unstack
# stack wide -> long # can't cope with factors
# unstack long -> wide  # can't cope with factors
mydataframe2 <- read.delim("D:\\web_sites_mine\\HIcourseweb new\\book2data\\ttest_2independent_long1.txt", header=TRUE)

unstacked_data <- unstack(mydataframe2) # works
str(unstacked_data)
unstacked_data   # wide format

stacked_data <- stack(unstacked_data)   # wide format
str(stacked_data)
stacked_data # long format

str(mydataframe)
mydataframe_fixed <- data.frame(value=mydataframe[,1], ind=as.numeric(mydataframe[,2]))
str(mydataframe_fixed)
stacked_data <- stack(mydataframe_fixed) # works
str(stacked_data)

# effect size - wide data
effectsize <- (mean(mydataframe$treatment) - mean(mydataframe$control))/
sapply(stack(mydataframe), sd) # using this stops error message when
# trying to produce sd for factor
effectsize


# effect size - long data
str(mydataframe2)
#'data.frame':   200 obs. of  2 variables:
# $ values: num  453 400 445 424 119 ...
# $ ind   : Factor w/ 2 levels "control","treatment": 2 2 2 2 2 2 2 2 2 2 ...

effectsize <- (mean(mydataframe2$values[mydataframe2$"ind" =="treatment"]) 
- mean(mydataframe2$values[mydataframe2$"ind" =="control"]))/sd(mydataframe2$values)
effectsize