rcbd {doebioresearch} R Documentation

## Analysis of Randomized Complete Block 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

rcbd(data, treatmentvector, replicationvector, MultipleComparisonTest)


### Arguments

 data dependent variables treatmentvector vector containing treatments replicationvector vector containing replications MultipleComparisonTest 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

### Examples

data<-data.frame(GFY=c(16,13,14,16,16,17,16,17,16,16,17,16,15,15,15,13,15,14,
16,14,15,14,15,17,18,15,15,15,14,14,14,14,15,15,13,15,14,14,13,13,13,12,15,12,15),
DMY=c(5,5,6,5,6,7,6,8,6,9,8,7,5,5,5,4,6,5,8,5,5,5,4,6,6,5,5,6,6,6,5,5,5,5,5,6,5,5,5,4,5,4,5,5,5),
Rep=rep(c("R1","R2","R3"),each=15),
Trt=rep(c("T1","T2","T3","T4","T5","T6","T7","T8","T9","T10","T11","T12","T13","T14","T15"),3))
#' #RCBD analysis with duncan test for GFY only
rcbd(data[1],data$Trt,data$Rep,2)
#RCBD analysis with duncan test for both GFY and DMY
rcbd(data[1:2],data$Trt,data$Rep,2)


[Package doebioresearch version 0.1.0 Index]