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))
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)
```

[Package

*agricolae*version 1.3-7 Index]