errorBarGraph(fit, mcadjust=FALSE, alpha = 0.05, cgtheme = TRUE, device="single", ...)
estimate
of the group,
where each group also has the same standard error (and sample size).
If the standard errors / variances are similar enough across the groups, the
visualization may still be effective even though the error bar
lengths will be approximations.
centralvar
discussion in the previous item, it may serve as
part of a visually useful approximation for other cases.
"log"
or
"original"
. If the default "log"
then the y-axis will be created
with a logarithmic spacing. The tick marks will be calculated accordingly and
expressed in the original scale of the estimates. The
estimates
vector must already be in the logarithmic scale.
""
.""
.0.05
, which
equates to a 95% confidence level. This
is just used for labelling purposes.
NULL
, which will examine each individual estimates
value and choose the
one that has the maximum number of digits after any trailing
zeroes are ignored. The max number of digits will be 4.NULL
.fit
method from the cg
package.
FALSE
.
If mcadjust=TRUE
is specified, there will be a delay,
usually just for a few seconds, due to computing time of the
critical point in order to create the error bar intervals.
0.05
so
that confidence levels are 95%.
TRUE
, ensures a trellis device is active with
limited color scheme. Namely background
,
strip.shingle
, and strip.background
are each set to "white"
.
"single"
"multiple"
"ask"
ask=TRUE
argument specified in par
so that
the user input confirmation is needed before the graphs are
drawn.
errorBarGraph
methods
code. Therefore any direct use of it needs to be done cautiously.mcadjust=TRUE
, a status message of
"Some time may be needed"
"as the critical point from the multcomp::summary.glht function call is calculated"
is displayed at the console. This computed critical point
is used for all subsequent p-value and confidence interval calculations.
multcomp
R package.Hothorn, T., Bretz, F., and Westfall, P. (2008). "Simultaneous Inference in General Parametric Models", Biometrical Journal, 50, 3, 346-363.
errorBarGraph.cgOneFactorFit
data(canine)
canine.data <- prepareCGOneFactorData(canine, format="groupcolumns",
analysisname="Canine",
endptname="Prostate Volume",
endptunits=expression(plain(cm)^3),
digits=1, logscale=TRUE, refgrp="CC")
canine.fit <- fit(canine.data)
errorBarGraph(canine.fit)
errorBarGraph(canine.fit, mcadjust=TRUE, model="olsonly")
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