Compute Descriptive Summary Statistics of Groups in a cgOneFactorData object
Description
Create a table of quantiles and other summary statistics of the data in a
cgOneFactorData
object.
Usage
1 2  ## S4 method for signature 'cgOneFactorData'
descriptiveTable(data, display = "print", ...)

Arguments
data 
A 
display 
One of three valid values:

... 
Additional arguments. Currently only one is valid:

Details
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 KaplanMeier
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.
Value
Creates an object of class cgOneFactorDescriptiveTable
, with the
following slots:
contents
The table of descriptive summary statistics for each group. See below for the data frame structure of the table.
settings
A list of settings carried from the
cgOneFactorData
data
object. These are used for theprint.cgOneFactorDescriptiveTable
method, invoked for example whendisplay="print"
.
The data frame structure of the descriptive table in a contents
slot consists of row.names
that specify the group, and these columns:
n
The sample size of the group.
Min
The minimum value of the group.
25%ile
The 25th percentile of the group, estimated with the
quantile
function.Median
The median value of the group.
75%ile
The 75th percentile of the group, estimated with the
quantile
function.Max
The maximum value of the group.
Mean
The arithmetic mean value of the group.
StdDev
The standard deviation value of the group.
StdErr
The standard error value of the group.
If logscale=TRUE
, then two additional columns are added:
GeoMean
The geometric mean value of the group.
SEGeoMean
The 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:
ncensored
The number of censored / incomplete observations.
ncomplete
The 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 rightcensoring and leftcensoring, respectively.
For censored data, KaplanMeier 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.
Note
Contact cg@billpikounis.net for bug reports, questions, concerns, and comments.
Author(s)
Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb]
References
Gentleman, R.C. and Crowley, J. (1991). "Graphical Methods for Censored Data", Journal of the American Statistical Association, Volume 86, 678683.
Examples
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="GMCSF (pg/ml)",
logscale=TRUE)
descriptiveTable(gmcsfcens.data)
