Description Usage Arguments Details Value Note Author(s) References Examples
Create a table of quantiles and other summary statistics of the data in a
cgOneFactorData object.
1 2 | ## S4 method for signature 'cgOneFactorData'
descriptiveTable(data, display = "print", ...)
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data |
A |
display |
One of three valid values:
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... |
Additional arguments. Currently only one is valid:
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The returned table contains quantiles, means, sample sizes, and
estimates of variability for each group. If censored data are present,
the estimated quantiles accomodate that with the Kaplan-Meier
method, following Gentleman and Crowley (1991) .
The number of censored / incomplete and number of complete observations
are also included when censored data is present in any of the groups.
If the logscale option is specified (either explicitly, or implicitly
from the cgOneFactorData object), then the geometric mean and
geometric standard error for each group are also included. See the Value section
below for details.
Creates an object of class cgOneFactorDescriptiveTable, with the
following slots:
contentsThe table of descriptive summary statistics for each group. See below for the data frame structure of the table.
settingsA list of settings carried from the
cgOneFactorData data object. These are used
for the print.cgOneFactorDescriptiveTable method,
invoked for example when display="print".
The data frame structure of the descriptive table in a contents
slot consists of row.names that specify the group, and these columns:
nThe sample size of the group.
MinThe minimum value of the group.
25%ileThe 25th percentile of the group, estimated
with the quantile function.
MedianThe median value of the group.
75%ileThe 75th percentile of the group, estimated
with the quantile function.
MaxThe maximum value of the group.
MeanThe arithmetic mean value of the group.
StdDevThe standard deviation value of the group.
StdErrThe standard error value of the group.
If logscale=TRUE, then two additional columns are added:
GeoMeanThe geometric mean value of the group.
SEGeoMeanThe estimated standard error associated withthe geometric mean. This is calculated with the Delta Method, and will particularly lose accuracy in its useful approximation once the standard error in the log scale exceeds 0.50. A warning message is issued when this occurs.
If censored data are present in the cgOneFactorData object,
then two more columns are added:
ncensoredThe number of censored / incomplete observations.
ncompleteThe number of complete observations.
These two ncensored and ncomplete quantities will add up
to n above and be placed
adjacent to it.
The presence of censored observations will convert columns such as the
Min and Max to character values, with the appropriate ">"
and "<" symbols for right-censoring and left-censoring, respectively.
For censored data, Kaplan-Meier estimates are used for the quantiles, as
proposed by Gentleman and Crowley (1991). The survreg::survfit
conventions are followed for interpolation of these quantiles.
With enough censored data
observations in a group, certain quantiles may not be estimable. If
any censored observations are present, the mean, geometric mean,
and associated standard errors will not be
calculated. The <NA> character representation is used.
Contact cg@billpikounis.net for bug reports, questions, concerns, and comments.
Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb]
Gentleman, R.C. and Crowley, J. (1991). "Graphical Methods for Censored Data", Journal of the American Statistical Association, Volume 86, 678-683.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | data(canine)
canine.data <- prepareCGOneFactorData(canine, format="groupcolumns",
analysisname="Canine",
endptname="Prostate Volume",
endptunits=expression(plain(cm)^3),
digits=1, logscale=TRUE, refgrp="CC")
descriptiveTable(canine.data)
## Remove the geometric mean and standard error columns
descriptiveTable(canine.data, logscale=FALSE)
## Censored Data
data(gmcsfcens)
gmcsfcens.data <- prepareCGOneFactorData(gmcsfcens, format="groupcolumns",
analysisname="cytokine",
endptname="GM-CSF (pg/ml)",
logscale=TRUE)
descriptiveTable(gmcsfcens.data)
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