actors

Information on 25 actors of a consultancy firm for which a sequence of e-mail
messages is observed (can be accessed through the 'events' data object).
The actor data is simulated based on information provided in
Mulder &amp; Leenders (2019). In the original data, 70 actors were involved. The
current data is a random sample of 25 actors.

datasets

Implementation of various default Bayes factors
for testing statistical hypotheses. The package is
intended for applied quantitative researchers in the
social and behavioral sciences, medical research,
and related fields. The Bayes factor tests can be
executed for statistical models such as
univariate and multivariate normal linear models,
generalized linear models, special cases of
linear mixed models, survival models, relational
event models. Parameters that can be tested are
location parameters (e.g., regression coefficients),
variances (e.g., group variances), and measures of
association (e.g,. bivariate correlations).
The statistical underpinnings are
described in
Mulder, Hoijtink, and Xin (2019) <arXiv:1904.00679>,
Mulder and Gelissen (2019) <arXiv:1807.05819>,
Mulder (2016) <DOI:10.1016/j.jmp.2014.09.004>,
Mulder and Fox (2019) <DOI:10.1214/18-BA1115>,
Mulder and Fox (2013) <DOI:10.1007/s11222-011-9295-3>,
Boeing-Messing, van Assen, Hofman, Hoijtink, and Mulder <DOI:10.1037/met0000116>,
Hoijtink, Mulder, van Lissa, and Gu, (2018) <DOI:10.31234/osf.io/v3shc>,
Gu, Mulder, and Hoijtink, (2018) <DOI:10.1111/bmsp.12110>,
Hoijtink, Gu, and Mulder, (2018) <DOI:10.1111/bmsp.12145>, and
Hoijtink, Gu, Mulder, and Rosseel, (2018) <DOI:10.1037/met0000187>.

Joris Mulder

BFpack

Flexible Bayes Factor Testing of Scientific Expectations

Caspar van Lissa

Xin Gu

Anton Olsson-Collentine

Florian Boeing-Messing

Donald R. Williams

Jean-Paul Fox

Janosch Menke

Barry Brown

James Lovato

Kathy Russell

Lapack 3.8 

Jack Dongarra

Jim Bunch

Cleve Moler

Gilbert Stewart

John Burkandt

Ashwith Rego

Alexander Godunov

Alan Miller

Jean-Pierre Moreau

The R Core Team 

actors function

dataframe (25 rows, 4 columns)<table><tr><td>
 actors$id </td>
<td> <code>integer</code> </td>
<td> ID of the employee, corresponding to
 the sender and receiver IDs in the events dataframe </td>
</tr><tr><td>
 actors$position </td>
<td> <code>numeric</code> </td>
<td> Hierarchical position of the employee,
 ranging from 1-4 </td>
</tr><tr><td>
 actors$division </td>
<td> <code>character</code> </td>
<td> Categorical variable, indicating the
 division of the employee </td>
</tr><tr><td>
 actors$location </td>
<td> <code>integer</code> </td>
<td> Categorical variable, indicating the location
 of the building the employee works in </td>
</tr></table>

Format

Actors from a consultancy firm — actors

Actors from a consultancy firm

actors$id	`integer`	ID of the employee, corresponding to the sender and receiver IDs in the events dataframe
actors$position	`numeric`	Hierarchical position of the employee, ranging from 1-4
actors$division	`character`	Categorical variable, indicating the division of the employee
actors$location	`integer`	Categorical variable, indicating the location of the building the employee works in

actors: Actors from a consultancy firm

Description

Usage

Arguments

Format

Details

References