demo/SPE.R

In ScottKnott: The ScottKnott Clustering Algorithm

##
## Example: Split-plot Experiment (SPE)
##

## The parameters can be: formula, aov, lm or lmer.

## Note: Upper case for factors and lowercase for levels

library(ScottKnott)
data(SPE)

## From: formula
## Main factor: SP
sk1 <- with(SPE,
            SK(y ~ blk + P*SP + Error(blk/P),
               data=dfm,
               which='SP'))
summary(sk1)

## Nested: p1/SP
sk2 <- with(SPE,
            SK(y ~ blk + P*SP + Error(blk/P),
               data=dfm,
               which='P:SP',
               fl1=1 ))
summary(sk2)
plot(sk2,
     di='sd',
     d.col='red',
     d.lty=3)

## Nested: sp1/P - it is necessary to inform how to combinate the errors
sk3 <- with(SPE,
            SK(y ~ blk + P*SP + Error(blk/P),
               data=dfm,
               which='SP:P',
               error='Within/blk:P',
               fl1=1))
summary(sk3)

## From: lm
lm1 <- with(SPE,
            lm(y ~ blk*P + P*SP,
               dfm))

sk4 <- SK(lm1,
          which='P:SP',
          fl1=1)

summary(sk4)

sk5 <- SK(lm1,
          which='SP:P',
          error='Within/blk:P',
          fl1=1)
summary(sk5)


## From: aov
av1 <- with(SPE,
            aov(y ~ blk + P*SP + Error(blk/P),
                data=dfm))
summary(av1)

## Main factor: SP
sk6 <- SK(av1,
          which='SP',
          sig.level=0.1)
summary(sk6)

## Main factor: P
## It is necessary to inform the appropriate error for the test
sk7 <- SK(av1,
          which='P',
          error='blk:P')

summary(sk7)

## Nested: p1/SP
## Testing SP inside of level one of P
sk8 <- SK(av1,
          which='P:SP',
          fl1=1)
summary(sk8)

## Nested: p2/SP
sk9 <- SK(av1,
          which='P:SP',
          fl1=2)
summary(sk9)

## Nested: p3/SP
sk10 <- SK(av1,
           which='P:SP',
           fl1=3)
summary(sk10)

## Nested: sp1/P - it is necessary to inform how to combinate the errors
sk11 <- SK(av1,
           which='SP:P',
           error='Within/blk:P',
           fl1=1)
summary(sk11)