strip.plot: Strip-Plot analysis

In agricolae: Statistical Procedures for Agricultural Research

Strip-Plot analysis

Description

The variance analysis of a strip-plot design is divided into three parts: the horizontal-factor analysis, the vertical-factor analysis, and the interaction analysis.

Usage

strip.plot(BLOCK, COL, ROW, Y)

Arguments

BLOCK	replications
COL	Factor column
ROW	Factor row
Y	Variable, response

Details

The strip-plot design is specifically suited for a two-factor experiment in which the desired precision for measuring the interaction effects between the two factors is higher than that for measuring the main efect two factors

Value

Data and analysis of the variance of the strip plot design.

Author(s)

Felipe de Mendiburu

References

Statistical procedures for agricultural research. Kwanchai A. Gomez, Arturo A. Gomez. Second Edition. 1984.

See Also

ssp.plot, sp.plot, design.split, design.strip

Examples

# Yield
library(agricolae)
data(huasahuasi)
YIELD<-huasahuasi$YIELD
market <- YIELD$y1da + YIELD$y2da
non_market <- YIELD$y3da
yield <- market + non_market
model<-with(YIELD,strip.plot(block, clon, trt, yield))
out1<-with(YIELD,LSD.test(yield,clon,model$gl.a,model$Ea))
oldpar<-par(mar=c(3,8,1,1),cex=0.8)
plot(out1,xlim=c(0,80),horiz=TRUE,las=1)
out2<-with(YIELD,LSD.test(yield,trt,model$gl.b,model$Eb))
plot(out2,xlim=c(0,80),horiz=TRUE,las=1)
par(oldpar)

agricolae documentation built on Oct. 23, 2023, 1:06 a.m.