View source: R/effectsMethods.r
print.sienaEffects | R Documentation |
Prints the major columns of the effects object. Or all, with any non-atomic columns listed separately.
## S3 method for class 'sienaEffects'
print(x, fileName = NULL, includeOnly=TRUE,
expandDummies = FALSE, includeRandoms = FALSE, dropRates=FALSE, ...)
## S3 method for class 'sienaEffects'
summary(object, fileName = NULL,
includeOnly=TRUE, expandDummies = FALSE, ...)
## S3 method for class 'summary.sienaEffects'
print(x, fileName = NULL, ...)
object |
An object of class |
x |
An object of class |
fileName |
Character string denoting file name if file output desired. |
includeOnly |
Boolean. If TRUE, only effects with the include flag TRUE will be printed. |
expandDummies |
Interpret the |
includeRandoms |
Boolean. If TRUE, also the
|
dropRates |
Boolean. If TRUE, do not print the rows for basic rate effects. |
... |
For extra arguments (none used at present). |
The function print.sienaEffects
prints details of the main
columns of the selected rows of the effects object.
If the effects object includes statistics for the
Generalized Method of Moments (GMoM), as included by function
includeGMoMStatistics
and for which type=gmm
,
the print consists of two parts: the first consists of the
included effects for the probability model, the second
of the statistics used for GMoM estimation.
The function summary.sienaEffects
checks the rows for valid
printing via print.data.frame
and excludes any that will
fail. The OK columns are printed first, followed by any others.
Output from either can be directed to a file by using the argument
filename
.
Ruth Ripley, modifications by Tom Snijders and Viviana Amati.
See https://www.stats.ox.ac.uk/~snijders/siena/
sienaEffects
,
getEffects
, includeEffects
,
includeGMoMStatistics
,
sienaTimeTest
,
effectsDocumentation
mynet1 <- sienaDependent(array(c(s501, s502, s503), dim=c(50, 50, 3)))
mybeh <- sienaDependent(s50a, type="behavior")
mycovar <- coCovar(rnorm(50))
mydyadcovar <- coDyadCovar(matrix(as.numeric(rnorm(2500) > 2), nrow=50))
mydata <- sienaDataCreate(mynet1, mybeh, mycovar, mydyadcovar)
myeff <- getEffects(mydata)
myeff
summary(myeff)
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