cg (version 1.0-4)

print.cgPairedDifferenceFit: Print One Factor Model Fit object with some format options

Description

Print a cgPairedDifferenceFit object, which contains fitted model information.

Usage

# S4 method for cgPairedDifferenceFit
print(x, title = NULL, endptname = NULL, ...)

Value

print.cgPairedDifferenceFit returns

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

Arguments

x

An cgPairedDifferenceFit object.

title

The title printed out with the fitted model information. If NULL, it is set to be "Fitted Models 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 fits are printed. This is the default when both fits are present in the cgPairedDifferenceFit object specified in the x argument.

"olsonly"

Only the ordinary classical least squares model fit is printed.

"rronly"

Only the resistant & robust model fit is printed.

Author

Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb]

Details

The object 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 print methods for individual fit classes, such as lm and rlm.

Note that show is an alias for print for this method. A showObj.cgPairedDifferenceFit method is defined to display the raw form of the object.

See Also

cgOneFactorFit, cgPairedDifferenceFit

Examples

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

print(anorexiaFT.fit)