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print.sienaEffects

Print methods for Siena effects objects


Description

Prints the major columns of the effects object. Or all, with any non atomic columns listed separately.

Usage

## 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, ...)

Arguments

object

An object of class sienaEffects.

x

An object of class sienaEffects or summary.sienaEffects as appropriate.

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 timeDummy column and show any effects which would be added by sienaTimeFix.

includeRandoms

Boolean. If TRUE, also the randomEffects column will be printed.

dropRates

Boolean. If TRUE, do not print the rows for basic rate effects.

...

For extra arguments (none used at present).

Value

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.

Author(s)

Ruth Ripley, modifications by Tom Snijders and Viviana Amati.

References

See Also

Examples

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)

RSiena

Siena - Simulation Investigation for Empirical Network Analysis

v1.3.0
GPL-2 | GPL-3 | file LICENSE
Authors
Tom A.B. Snijders [cre, aut] (<https://orcid.org/0000-0003-3157-4157>), Ruth Ripley [aut], Christian Steglich [aut, ctb] (<https://orcid.org/0000-0002-9097-0873>), Johan Koskinen [aut, ctb] (<https://orcid.org/0000-0002-6860-325X>), Nynke Niezink [aut, ctb], Viviana Amati [aut, ctb] (<https://orcid.org/0000-0003-1190-1237>), Christoph Stadtfeld [ctb] (<https://orcid.org/0000-0002-2704-2134>), James Hollway [ctb] (IHEID, <https://orcid.org/0000-0002-8361-9647>), Per Block [ctb], Robert Krause [ctb], Charlotte Greenan [ctb], Josh Lospinoso [ctb], Michael Schweinberger [ctb] (<https://orcid.org/0000-0003-3649-5386>), Mark Huisman [ctb], Krists Boitmanis [ctr], Felix Schoenenberger [ctb], Mark Ortmann [ctb], Marion Hoffman [ctb], Robert Hellpap [ctb], Alvaro Uzaheta [ctb]
Initial release
2021-05-02

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