cg (version 1.0-2)

qqGraph.cgPairedDifferenceFit: Quantile-Quantile (QQ) Graphs of a cgPairedDifferenceFit object

Description

Create a Q-Q Gaussian graph of the residuals of a cgPairedDifferenceFit object

Usage

## S3 method for class 'cgPairedDifferenceFit':
qqGraph(fit, line=TRUE, cgtheme = TRUE, device = "single", \dots)

Arguments

fit

A fit object of class cgPairedDifferenceFit.

line

Add a line through the estimated 25th and 75th percentiles, when set to the default TRUE.

cgtheme

When set to the default TRUE, ensures a trellis device is active with limited color scheme. Namely, background, strip.shingle, and strip.background are each set to "white".

device

Can be one of three values: [object Object],[object Object],[object Object]

...

Additional arguments. One is currently valid: [object Object]

Value

• qqGraph.cgPairedDifferenceFit returns an invisible NULL. The main purpose is the side effect of graphing to the current device.

concept

• quantile-quantile
• residual diagnostics

Details

The heading for the graph is taken from the cgPairedDifferenceData object, which prepareCGPairedDifferenceData sets from its analysisname argument. The label for the Y-axis is taken from the cgPairedDifferenceData object, which prepareCGPairedDifferenceData sets from its endptname argument. The number of decimal places printed in the ticks on the Y-axis is taken from the cgPairedDifferenceData object, which prepareCGPairedDifferenceData sets from its digits argument. The minimum and maximum values from the range of the residuals are respectively labeled in the bottom and top left corners of the graph region.

See Also

qqline

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(anorexiaFT.data)

qqGraph(anorexiaFT.fit)

qqGraph(anorexiaFT.fit, model="olsonly")