Description Usage Arguments Details Value Note Author(s) References Examples
Fits a paired difference model based
on the cgPairedDifferenceData object. The
created object is designed for paired samples
collected data, and is of class cgPairedDifferenceFit.
1 2 |
data |
A data object of class |
type |
Type of model to fit, represented by a character
value. The default value is
|
... |
Additional arguments, both optional, that are allowed to be specified dependent on
the choice of the
|
In the current version of the cg package, most default settings
for rlm are kept for the
fit.cgPairedDifferenceData method wrapper call when
type="rr", with no capability to choose
another value for an arguments such as psi, scale.est,
and k2. The method argument is set to "MM".
Creates an object of class cgPairedDifferenceFit, with the
following slots:
olsfitThe contents of a lm fit to the
data. This is always populated with an lm object
no matter the choice of the type argument, such as code="rr".
rrfitThe contents of a rlm fit to the
data, housed as a rrfit class object.
If type="rr" is not selected, then this is set
to a simple character value of "No fit was selected.".
settingsA list of properties carried as-is from the
data argument object of class
cgPairedDifferenceData.
In particular,
if zeroscore is specified as a non-NULL number in
the cgPairedDifferenceData object in the data
argument, then a score value near zero was derived to replace
all zeroes for subsequent
log-scale analyses. Alternatively, if addconstant is specified
as a non-NULL number in the
cgPairedDifferenceData object in the data
argument, then a value was added to shift up all observations for subsequent
log-scale analyses.
Contact cg@billpikounis.net for bug reports, questions, concerns, and comments.
Bill Pikounis [aut, cre, cph], John Oleynick [aut], Eva Ye [ctb]
Venables, W. N. and Ripley, B. D. (2002), Modern Applied Statistics with S. Fourth edition. Springer.
1 2 3 4 5 6 7 8 | 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")
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