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:
olsfit
The 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"
.
rrfit
The 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."
.
settings
A 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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