Compute Descriptive Summary Statistics of Groups in a cgPairedDifferenceData object
Create a table of quantiles and other summary statistics of the data in a
One of three valid values:
Additional arguments. Currently only one is valid:
The returned table contains quantiles, means, sample sizes, and
estimates of variability for each group, and also for the paired
It also presents the same
summary measures for the paired differences from the groups.
logscale option is specified (either explicitly, or implicitly
cgPairedDifferenceData object), then the geometric mean and
geometric standard error for each of the two groups are included. Also
included are summary measures of the ratio and percent forms of the paired
differences. See the Value section below for details.
Creates an object of class
cgPairedDifferenceDescriptiveTable, with the
The table of descriptive summary statistics for each group, and also for paired differences. See below for the data frame structure of the table.
A list of settings carried from the
dataobject. These are used for the
print.cgPairedDifferenceDescriptiveTablemethod, invoked for example when
The data frame structure of the descriptive table in a
slot consists of
row.names that specify the group or paired
difference, and these columns:
The sample size.
The minimum value.
The 25th percentile, estimated with the
The median value.
The 75th percentile, estimated with the
The maximum value.
The arithmetic mean value.
The standard deviation value.
The standard error value.
logscale=TRUE, then two additional columns are added:
The geometric mean value of the group.
The estimated standard error associated with the 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.
The third row of simple difference summaries
SEGeoMean are set to <NA>.
Fourth and fifth rows are also added with summaries of the paired
ratio differences and percent differences. The
StdErr values are set to <NA> in these two rows.
SEGeoMean values are calculated via the
the Delta Method, with the same caveats described above.
Contact email@example.com for bug reports, questions, concerns, and comments.
Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb]
1 2 3 4 5 6 7 8 9 10 11 12 13 14
data(anorexiaFT) anorexiaFT.data <- prepareCGPairedDifferenceData(anorexiaFT, format="groupcolumns", analysisname="Anorexia FT", endptname="Weight", endptunits="lbs", expunitname="Patient", digits=1, logscale=TRUE) descriptiveTable(anorexiaFT.data) ## Remove the geometric mean and standard error columns, ## and the Ratio / Percent Rows, since they are no longer applicable. descriptiveTable(anorexiaFT.data, logscale=FALSE)
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