doebioresearch (version 0.1.0)

frbd3fact: Analysis of Factorial Randomized Block Design for 3 factors

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

frbd3fact(
  data,
  replicationvector,
  fact.A,
  fact.B,
  fact.C,
  Multiple.comparison.test
)

Arguments

data

dependent variables

replicationvector

vector containing replications

fact.A

vector containing levels of first factor

fact.B

vector containing levels of second factor

fact.C

vector containing levels of third factor

Multiple.comparison.test

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

Value

ANOVA, interpretation of ANOVA, R-square, normality test result, SEm, SEd and multiple comparison test result for the factors as well as the interaction.

Examples

# NOT RUN {
data(factorialdata)
#FRBD analysis along with dunccan test for two dependent var.
frbd3fact(factorialdata[5:6],factorialdata$Replication,factorialdata$Nitrogen,
factorialdata$Phosphorus,factorialdata$Potassium,2)
# }