Summary display of a Paired Difference Model Fit object with some format options

Description

Summary printing of a cgPairedDifferenceFit object, which contains fitted model information.

Usage

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## S4 method for signature 'cgPairedDifferenceFit'
summary(object, title = NULL, endptname = NULL, ...)

Arguments

object

An cgPairedDifferenceFit object.

title

The title printed out with the summary of the fitted model(s). If NULL, it is set to be "Fitted Model Summaries of" the analysisname value in the settings slot of the cgPairedDifferenceFit object.

endptname

The endpoint name, printed out with the fitted model information. If NULL, it is set to the endptname value in the settings slot of the cgPairedDifferenceFit object.

...

Additional arguments. Only one is currently valid:

model

For cgPairedDifferenceFit objects that have output derived from classical least squares lm or resistant & robust rlm fits, the following argument values are possible:

"both"

Both the ordinary classical least squares and resistant & robust model fit summaries are printed. This is the default when both fits are present in the cgPairedDifferenceFit object specified in the object argument.

"olsonly"

Only the ordinary classical least squares model fit summary is printed.

"rronly"

Only the resistant & robust model fit summary is printed.

Details

The object summary is printed using a mix of cat and print calls. See cgPairedDifferenceFit for details of the *fit and other object slots.

This method simply echoes summary methods for individual fit classes, such as lm and rlm.

Value

summary.cgPairedDifferenceFit returns invisible. The main purpose is the side effect of printing to the current output connection, which is typically the console.

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]

See Also

cgPairedDifferenceFit

Examples

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

summary(anorexiaFT.fit)

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