downweightedTable: Create a table of downweighted observations from a Resistant & Robust fit.

Description

Create a table of downweighted observations in a resistant & robust fit with the cg package.

Usage

downweightedTable(fit, cutoffwt, display="print", ...)

Arguments

fit

A fit object created with a fit method from the cg package.

cutoffwt

It has no default and must be specified as a numeric between 0 and 1 exclusive. It is a threshold. All observations that fall beneath the threshold will be identified. For example, a cutoffwt=0.90 will yield those observations that were downweighted by at least 10%.

display

One of three valid values:

"print": The default value; It calls a print method for the created downweightedTable object, which is a formatted text output of the table(s).
"none": Supresses any printing. Useful, for example, when just assignment of the resulting object is desired.
"show": Calls the default showDefault method, which will just print out the downweightedTable components.

...

Additional arguments, depending on the specific method written for the object. See the method-specific documentation for additional details.

Value

A method-specific downweightedTable object is returned. See the specific methods for discussion of return values.

References

Venables, W. N. and Ripley, B. D. (2002), Modern Applied Statistics with S. Fourth edition. Springer.

Examples

Run this code

#### One Factor data

data(canine)
canine.data <- prepareCGOneFactorData(canine, format="groupcolumns",
                                      analysisname="Canine",
                                      endptname="Prostate Volume",
                                      endptunits=expression(plain(cm)^3),
                                      digits=1, logscale=TRUE, refgrp="CC")
canine.fit <- fit(canine.data)

canine.dwtable <- downweightedTable(canine.fit, cutoff=0.95)

downweightedTable(canine.fit, cutoff=0.75) ## No observation
                                           ## downweighted at least 25%

## Paired Difference data

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

downweightedTable(anorexiaFT.fit, cutoffwt=0.25) ## No observation

downweightedTable(anorexiaFT.fit, cutoffwt=0.75) ## downweighted at least 25%