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

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))
    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)

[Package agricolae version 1.2-9 Index]