cg (version 1.0-2)

prepareCGPairedDifferenceData: Prepare data object from a data frame for Paired Samples evaluations

Description

The function prepareCGPairedDifferenceData reads in a data frame and settings in order to create a cgPairedDifferenceData object. The created object is designed to have exploratory and fit methods applied to it.

Usage

prepareCGPairedDifferenceData(dfr, format = "listed", analysisname = "",
 endptname = "", endptunits = "", logscale = TRUE, zeroscore = NULL,
 addconstant = NULL, digits = NULL, expunitname= "",
 refgrp = NULL, stamps = FALSE)

Arguments

dfr

A valid data frame, see the format argument.

format

Default value of "listed". Either "listed" or "groupcolumns" must be used. Abbreviations of "l" or "g", respectively, or otherwise sufficient matching values can be used:

analysisname

Optional, a character text or math-valid expression that will be set for default use in graph title and table methods. The default value is the empty "".

endptname

Optional, a character text or math-valid expression that will be set for default use as the y-axis label of graph methods, and also used for table methods. The default value is the empty "".

endptunits

Optional, a character text or math-valid expression that can be used in combination with the endptname argument. Parentheses are automatically added to this input, which will be added to the end of the endptname character

logscale

Apply a log-transformation to the data for evaluations. The default value is TRUE.

zeroscore

Optional, replace response values of zero with a derived or specified numeric value, as an approach to overcome the presence of zeroes when evaluation in the logarithmic scale (logscale=TRUE) is specified. The def

addconstant

Optional, add a numeric constant to all response values, as an approach to overcome the presence of zeroes when evaluation in the logarithmic scale logscale=TRUE is desired. The default value is NULL.

digits

Optional, for output display purposes in graphs and table methods, values will be rounded to this numeric value. Only the integers of 0, 1, 2, 3, and 4 are accepted. No rounding is done during any calculations. The default value is

expunitname

Optional, a character text that will be set for default use as the experimental unit label of graph methods, and also used for table methods. The default value is the empty "".

refgrp

Optional, specify one of the factor levels to be the reference group, such as a control group. The default value is NULL, which will just use the first level determined in the data fra

stamps

Optional, specify a time stamp in graphs, along with cg package version identification. The default value is FALSE.

Value

• A cgPairedDifferenceData object is returned, with the following slots:
• dfr
  The original input data frame that is the specified value of the dfr argument in the function call.
• dfru
  Processed version of the input data frame, which will be used for the various evaluation methods.
• dfr.gcfmt
  A groupcolumns version of the input data frame with an additional column of the differences between groups, where the regfrp column of values is the subtrahend (second term) in the subtraction.
• settings
  A list of properties associated with the data frame: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Details

[object Object],[object Object],[object Object]

References

Tukey, J.W., Ciminera, J.L., and Heyse, J.F. (1985). "Testing the Statistical Certainty of a Response to Increasing Doses of a Drug," Biometrics, Volume 41, 295-301. Chambers, J.M, and Hastie, T.R. (1992), Statistical Modeling in S. Chapman&Hall/CRC.

See Also

prepare

Examples

data(anorexiaFT)
anorexiaFT.data <- prepareCGPairedDifferenceData(anorexiaFT, format="groupcolumns",
                                                 analysisname="Anorexia FT",
                                                 endptname="Weight",
                                                 endptunits="lbs",
                                                 expunitname="Patient",
                                                 digits=1, logscale=TRUE)