sp.plot {agricolae} | R Documentation |
The variance analysis of a split plot design is divided into two parts: the plot-factor analysis and the sub-plot factor analysis.
sp.plot(block, pplot, splot, Y)
block |
replications |
pplot |
main-plot Factor |
splot |
sub-plot Factor |
Y |
Variable, response |
The split-plot design is specifically suited for a two-factor experiment on of the factors is assigned to main plot (main-plot factor), the second factor, called the subplot factor, is assigned into subplots. The model is mixed, the blocks are random and the study factors are fixed applied according to the design.
ANOVA: Splip plot analysis
Felipe de Mendiburu
Statistical procedures for agricultural research. Kwanchai A. Gomez, Arturo A. Gomez. Second Edition. 1984.
ssp.plot
, strip.plot
, design.split
,
design.strip
library(agricolae) data(plots) model<-with(plots,sp.plot(block,A,B,yield)) # with aov plots[,1]<-as.factor(plots[,1]) AOV <- aov(yield ~ block + A*B + Error(block/A),data=plots) summary(AOV)