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agricolae (version 1.0-9)

strip.plot: 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(BLOCKS, COL, ROW, Y)

Arguments

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

Value

  • BLOCKSvector, numeric
  • COLvector, numeric
  • ROWvector, numeric
  • Yvector, numeric

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

References

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

Examples

Run this code
# Yield
library(agricolae)
data(huasahuasi)
attach(huasahuasi)
YIELD<-huasahuasi$YIELD
attach(YIELD)
market <- y1da + y2da
non_market <- y3da
yield <- market + non_market
model<-strip.plot(block, clon, trt, yield)
comparison<-LSD.test(yield,clon,model$gl.a,model$Ea)
comparison<-LSD.test(yield,trt,model$gl.b,model$Eb)
# simple effects
out<-by(yield,trt, function(x) LSD.test(x, clon, model$gl.c, model$Ec))
out

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