R: Strip-Plot analysis

strip.plot {agricolae} | R Documentation

## 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

`BLOCK` | vector, numeric
`COL` | vector, numeric
`ROW` | vector, numeric
`Y` | vector, numeric

### 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))
    comparison<-with(YIELD,LSD.test(yield,clon,model$gl.a,model$Ea))
    comparison<-with(YIELD,LSD.test(yield,trt,model$gl.b,model$Eb))
    # simple effects
    A<-model$data
    a<-nlevels(A$clon)
    b<-nlevels(A$trt)
    r<-nlevels(A$block)
    Ea<-model$Ea; Eb<-model$Ec; Ec<-model$Ec;
    gla<-model$gl.a; glb<-model$gl.b; glc<-model$gl.c;
    B <-tapply.stat(A[,4],A[,2:3],mean)
    std<-tapply.stat(A[,4],A[,2:3],function(x) sd(x)/sqrt(length(x)))
    B<-data.frame(B[,1:2],yield=B[,3],std=std[,3])
    cmab<-(b-1)*Ec + Ea
    cmba<-(a-1)*Ec + Eb
    # order.group
    # Tukey
    ta <- qtukey(0.95,a,gla)
    tb <- qtukey(0.95,b,glb)
    tc <- qtukey(0.95,a*b,glc)
    tab<- ((b-1)*Ec*tc + Ea*ta)/cmab
    tba<- ((a-1)*Ec*tc + Eb*tb)/cmba
    # Comparison of clones by treatment
    groups<-by(B,B[,2], function(x) order.group(x$clon,x$yield,N=b*r, cmab,tab,
            std.err=x$std,parameter=0.5,console=FALSE))
    groups
    # Comparison of treatments by clon
    groups<-by(B,B[,1], function(x) order.group(x$trt,x$yield,N=a*r,cmba,tba,
            std.err=x$std,parameter=0.5,console=FALSE))
    groups
    # LSD t-student
    ta <- qt(0.975,gla)
    tb <- qt(0.975,glb)
    tc <- qt(0.975,glc)
    tab<- ((b-1)*Ec*tc + Ea*ta)/cmab
    tba<- ((a-1)*Ec*tc + Eb*tb)/cmba
    # Comparison of clones by treatment
    groups<-by(B,B[,2], function(x) order.group(x$clon,x$yield,N=b*r,cmab,tab,
            std.err=x$std,console=FALSE))
    groups
    # Comparison of treatments by clon
    groups<-by(B,B[,1], function(x) order.group(x$trt,x$yield,N=a*r,cmba,tba,
            std.err=x$std,console=FALSE))
    groups

[Package agricolae version 1.2-6 Index]