View source: R/dunnet_function.R
dunnett | R Documentation |
The function performs the Dunnett test
dunnett(
trat,
resp,
control,
model = "DIC",
block = NA,
column = NA,
line = NA,
alpha.t = 0.05,
pointsize = 5,
pointshape = 21,
linesize = 1,
labelsize = 4,
textsize = 12,
errorsize = 1,
widthsize = 0.2,
label = "Response",
fontfamily = "sans"
)
trat |
Numerical or complex vector with treatments |
resp |
Numerical vector containing the response of the experiment. |
control |
Treatment considered control (write identical to the name in the vector) |
model |
Experimental design (DIC, DBC or DQL) |
block |
Numerical or complex vector with blocks |
column |
Numerical or complex vector with columns |
line |
Numerical or complex vector with lines |
alpha.t |
Significance level (default is 0.05) |
pointsize |
Point size |
pointshape |
Shape |
linesize |
Line size |
labelsize |
Label size |
textsize |
Font size |
errorsize |
Errorbar size |
widthsize |
Width errorbar |
label |
Variable label |
fontfamily |
font family |
I return the Dunnett test for experiments in a completely randomized design, randomized blocks or Latin square.
Do not use the "-" symbol or space in treatment names
#====================================================
# complete randomized design
#====================================================
data("pomegranate")
with(pomegranate,dunnett(trat=trat,resp=WL,control="T1"))
#====================================================
# randomized block design in factorial double
#====================================================
library(AgroR)
data(cloro)
attach(cloro)
respAd=c(268, 322, 275, 350, 320)
a=FAT2DBC.ad(f1, f2, bloco, resp, respAd,
ylab="Number of nodules",
legend = "Stages",mcomp="sk")
data=rbind(data.frame(trat=paste(f1,f2,sep = ""),bloco=bloco,resp=resp),
data.frame(trat=c("Test","Test","Test","Test","Test"),
bloco=unique(bloco),resp=respAd))
with(data,dunnett(trat = trat,
resp = resp,
control = "Test",
block=bloco,model = "DBC"))
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