Description Usage Arguments Details Value Note Author(s) References Examples
Create a table of estimated group means based on the cgOneFactorFit object. Standard errors and confidence intervals are added. A cgOneFactorGrpSummaryTable class object is created.
1 2  ## S4 method for signature 'cgOneFactorFit'
grpSummaryTable(fit, mcadjust=FALSE, alpha=0.05, display="print", ...)

fit 
A fit object of class 
mcadjust 
Do a multiple comparisons adjustment, based on the simultaneous
inference capabilities of the multcomp package. See Details
below. The default value is 
alpha 
Significance level, by default set to 
display 
One of three valid values:

... 
Additional arguments. Only one is currently valid:
For other possible 
When 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 pvalue and confidence interval
calculations.
The multcomp package provides a unified way to calculate critical points based on the comparisons of interest in a "family". Thus a user does not need to worry about choosing amongst the myriad names of multiple comparison procedures.
Creates an object of class cgOneFactorGrpSummaryTable
, with the
following slots:
ols.grps
The table of group estimates based on the
olsfit
component of the cgOneFactorFit
,
unless model="rronly"
is specified. In that case the slot
value is NULL
. Will not be appropriate in
the case where a valid aftfit
component is present in the
cgOneFactorFit
object. See below for the data frame structure
of the table.
rr.grps
The table of group estimates based on the
rrfit
component of the cgOneFactorFit
object, if a valid resistant & robust fit object is present.
If rrfit
is a simple character value of
"No fit was selected."
, or model="olsonly"
was
specified, then the value is NULL
. See below for the data frame structure
of the table.
aft.grps
The table of group estimates based on the
aftfit
component of the cgOneFactorFit
object if a valid accelerated failure time fit object is present.
If aftfit
is a simple character value of
"No fit was selected."
, then the value is NULL
.
See below for the data frame structure
of the table.
uv.grps
The table of group estimates based on the
uvfit
component of the cgOneFactorFit
object if a valid unequal variances fit object is present.
If uvfit
is a simple character value of
"No fit was selected."
, then the value is NULL
.
See below for the data frame structure
of the table.
settings
A list of settings carried from the
cgOneFactorFit
fit
object, and the addition
of some specified arguments in the method call above: alpha
and mcadjust
. These are used
for the print.cgOneFactorGrpSummaryTable
method,
invoked for example when
display="print"
.
The data frame structure of the comparisons table in a *.comprs
slot consists of row.names
that specify group name (factor
level), and these columns:
estimate
The estimated group mean. If settings$endptscale=="log"
in the
fit
object, this will be backtransformed to a geometric mean.
se
The estimated standard error of the group mean
estimate
. If settings$endptscale=="log"
in the
fit
object, this estimate will be based on the Delta
method, and will begin to be a poor approximation when the
standard error in the logscale exceeds 0.50.
lowerci
The lower 100 * (1alpha
) % confidence limit of the
group mean estimate
. With the default alpha=0.05
,
this is 95%. If settings$endptscale=="log"
in the
fit
object, the confidence limit is first computed in the
logarithmic scale of analysis, and then backtransformed to the
original scale.
upperci
The upper 100 * (1alpha
) % confidence limit of the
difference estimate
. With the default alpha=0.05
,
this is 95%. If settings$endptscale=="log"
in the
fit
object, the confidence limit is first computed in the
logarithmic scale of analysis, and then backtransformed to the
original scale.
Contact cg@billpikounis.net for bug reports, questions, concerns, and comments.
Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb]
Hothorn, T., Bretz, F., Westfall, P., Heiberger, R.M., and
Schuetzenmeister, A. (2010). The multcomp
package.
Hothorn, T., Bretz, F., and Westfall, P. (2008). "Simultaneous Inference in General Parametric Models", Biometrical Journal, 50, 3, 346363.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22  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)
grpSummaryTable(canine.fit)
grpSummaryTable(canine.fit, mcadjust=TRUE, model="olsonly")
data(gmcsfcens)
gmcsfcens.data < prepareCGOneFactorData(gmcsfcens, format="groupcolumns",
analysisname="cytokine",
endptname="GMCSF (pg/ml)",
logscale=TRUE)
gmcsfcens.fit < fit(gmcsfcens.data, type="aft")
grpSummaryTable(gmcsfcens.fit)

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.
Please suggest features or report bugs in the GitHub issue tracker.
All documentation is copyright its authors; we didn't write any of that.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.