doebioresearch (version 0.1.0)

splitplot: Analysis of Split plot design

Description

The function gives ANOVA, R-square of the model, normality testing of residuals, SEm (standard error of mean), SEd (standard error of difference), interpretation of ANOVA results and multiple comparison test for means.

Usage

splitplot(data, block, main.plot, sub.plot, mean.comparison.test)

Arguments

data

dependent variables

block

vector containing replications

main.plot

vector containing main-plot levels

sub.plot

vector containing sub-plot levels

mean.comparison.test

0 for no test, 1 for LSD test, 2 for Dunccan test and 3 for HSD test

Value

ANOVA, interpretation of ANOVA, R-square, normality test result, SEm, SEd and multiple comparison test result

Examples

# NOT RUN {
data(splitdata)
#Using Date of sowing as Main-plot factor and varieties as sub-plot factor and using LSD test
#Split plot analysis with LSD test for Yield
splitplot(splitdata[4],splitdata$Replication,splitdata$Date_of_Sowing,splitdata$Varities,1)
#Split plot analysis with LSD test for both Yield and Plant Height
splitplot(splitdata[4:5],splitdata$Replication,splitdata$Date_of_Sowing,splitdata$Varities,1)
# }