# NOT RUN {
##
## Examples:Randomized Complete Block Design (RCBD)
## More details: demo(package='TukeyC')
##
## The parameters can be: formula, aov, lm, aovlist and lmerMod
data(RCBD)
## From: formula
tk1 <- with(RCBD,
TukeyC(y ~ blk + tra,
data=dfm,
which='tra'))
summary(tk1)
## From: merMod
## This class is specific of the lme4 package.
# }
# NOT RUN {
if(require(lme4)){
lmer1 <- with(RCBD,
lmer(y ~ (1|blk) + tra,
data=dfm))
tk2 <- TukeyC(lmer1,
which='tra')
summary(tk2)
}
# }
# NOT RUN {
##
## Example: Latin Squares Design (LSD)
## More details: demo(package='TukeyC')
##
data(LSD)
## From: formula
tk3 <- with(LSD,
TukeyC(y ~ rows + cols + tra,
data=dfm,
which='tra'))
summary(tk3)
## From: aov
av1 <- with(LSD,
aov(y ~ rows + cols + tra,
data=dfm))
tk4 <- TukeyC(av1,
which='tra')
summary(tk4)
## From: lm
lm1 <- with(LSD,
lm(y ~ rows + cols + tra,
data=dfm))
tk5 <- TukeyC(lm1,
which='tra')
summary(tk5)
##
## Example: Factorial Experiment (FE)
## More details: demo(package='TukeyC')
##
data(FE)
## From: formula
## Main factor: N
tk6 <- with(FE,
TukeyC(y ~ blk + N*P*K,
data=dfm,
which='N'))
summary(tk6)
## Nested: p1/N
# From: formula
n_tk1 <- with(FE,
TukeyC(y ~ blk + N*P*K,
data=dfm,
which='P:N',
fl1=1))
summary(n_tk1)
## Nested: p2/N
# From: lm
lm2 <- with(FE,
lm(y ~ blk + N*P*K,
dfm))
n_tk2 <- with(FE,
TukeyC(lm2,
which='P:N',
fl1=2))
summary(n_tk2)
## Nested: n1/P
# From: aov
av2 <- with(FE,
aov(y ~ blk + N*P*K,
dfm))
n_tk3 <- with(FE,
TukeyC(av2,
which='N:P',
fl1=1))
summary(n_tk3)
# From: merMod
# }
# NOT RUN {
if(require(lme4)){
lmer2 <- with(FE,
lmer(y ~ (1|blk) + N*P*K,
dfm))
n_tk4 <- with(FE,
TukeyC(lmer2,
which='N:P',
fl1=1))
summary(n_tk4)
}
# }
# NOT RUN {
##
## Example: Split-plot Experiment (SPET)
## More details: demo(package='TukeyC')
##
data(SPET)
## From lm
lm3 <- with(SPET,
lm(y ~ blk*tra + tra*year,
dfm))
# crotgrantiana/year
sp_tk1 <- TukeyC(lm3,
which='tra:year',
fl1=1)
summary(sp_tk1)
# year1/tra
# It is necessary to set year error with trat error in the order of the "which" argument.
# It is necessary to inform how to combinate the errors
sp_tk2 <- TukeyC(lm3,
which='year:tra',
error='Residuals/blk:tra',
fl1=1)
summary(sp_tk2)
# From merMod
# Onty tra
# }
# NOT RUN {
if(require(lme4)){
lmer3 <- with(SPET,
lmer(y ~ blk + (1|blk:tra) + tra*year,
dfm))
# comparison only tra
sp_tk3 <- TukeyC(lmer3,
which = 'tra',
error = 'blk:tra')
summary(sp_tk3)
# year1/tra
sp_tk4 <- TukeyC(lmer3,
which='year:tra',
error='Residual/blk:tra',
fl1=1)
summary(sp_tk4)
}
# }
# NOT RUN {
## Example: Split-split-plot Experiment (SSPE)
## More details: demo(package='TukeyC')
##
data(SSPE)
## From: formula
## Main factor: P
## It is necessary to inform the appropriate error for the test
ssp_tk1 <- with(SSPE,
TukeyC(y ~ blk + P*SP*SSP + Error(blk/P/SP),
data=dfm,
which='P',
error='blk:P'))
summary(ssp_tk1)
## Main factor: SP
## It is necessary to inform the appropriate error for the test
ssp_tk2 <- with(SSPE,
TukeyC(y ~ blk + P*SP*SSP + Error(blk/P/SP),
data=dfm,
which='SP',
error='blk:P:SP'))
summary(ssp_tk2)
## Main factor: SSP
ssp_tk3 <- with(SSPE,
TukeyC(y ~ blk + P*SP*SSP + Error(blk/P/SP),
data=dfm,
which='SSP'))
summary(ssp_tk3)
## From: aov
## Main factor: SSP
av3 <- with(SSPE,
aov(y ~ blk + P*SP*SSP + Error(blk/P/SP),
data=dfm))
ssp_tk4 <- TukeyC(av3,
which='SSP')
summary(ssp_tk4)
## Nested: p1/SP
## It is necessary to inform the appropriate error for the test
ssp_tk5 <- TukeyC(av3,
which='P:SP',
error='blk:P:SP',
fl1=1)
summary(ssp_tk5)
## Nested: p1/SSP
ssp_tk6 <- TukeyC(av3,
which='P:SSP',
fl1=1)
summary(ssp_tk6)
## Nested: p1/sp1/SSP
## Testing SSP inside of level one of P and level one of SP
ssp_tk7 <- TukeyC(av3,
which='P:SP:SSP',
fl1=1,
fl2=1)
summary(ssp_tk7)
## Nested: p2/sp1/SSP
ssp_tk8 <- TukeyC(av3,
which='P:SP:SSP',
fl1=2,
fl2=1)
summary(ssp_tk8)
## Nested: sp1/P
## It is necessary to inform the appropriate error for the test
ssp_tk9 <- TukeyC(av3,
which='SP:P',
error='blk:P:SP/blk:P',
fl1=1)
summary(ssp_tk9)
## Nested: ssp1/SP
ssp_tk10 <- TukeyC(av3,
which='SSP:SP',
error='Within/blk:P:SP',
fl1=1)
summary(ssp_tk10)
## Nested: ssp1/sp1/P
## It is necessary to inform the appropriate error for the test
ssp_tk11 <- TukeyC(av3,
which='SSP:SP:P',
error='Within/blk:P:SP/blk:P',
fl1=1,
fl2=1)
summary(ssp_tk11)
## UNBALANCED DATA
## The average are adjusted by "Least-Square-Means" methodology.
## From: formula
data(CRD2)
uCRD2 <- CRD2$dfm
uCRD2[c(3, 5, 10, 44, 45), 3] <- NA
utk1 <- TukeyC(y ~ x,
data=uCRD2,
which='x')
summary(utk1)
## From: lm
ulm1 <- lm(y ~ x,
data=uCRD2)
utk2 <- TukeyC(ulm1,
which='x')
summary(utk2)
## Factorial Experiments
## Nested: p1/N
# From: lm
uFE <- FE$dfm
uFE[c(3, 6, 7, 20, 31, 32), 5] <- NA
ulm2 <- lm(y ~ blk + N*P*K,
uFE)
## Nested: p1/N
utk3 <- TukeyC(ulm2,
data=uFE,
which='P:N',
fl1=1)
summary(utk3)
## Nested: p2/n2/K
utk4 <- TukeyC(ulm2,
data=uFE,
which='P:N:K',
fl1=2,
fl2=2)
summary(utk4)
# }
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