Title: Multiverse Analysis of Multinomial Processing Tree Models
Statistical or cognitive modeling usually requires a number of more or less
arbitrary choices creating one specific path through a 'garden of forking paths'.
The multiverse approach (Steegen, Tuerlinckx, Gelman, & Vanpaemel, 2016,
<doi:10.1177/1745691616658637>) offers a principled alternative in which results
for all possible combinations of reasonable modeling choices are reported.
MPTmultiverse performs a multiverse analysis for multinomial processing tree
(MPT, Riefer & Batchelder, 1988, <doi:10.1037/0033-295X.95.3.318>) models combining
maximum-likelihood/frequentist and Bayesian estimation approaches with
different levels of pooling (i.e., data aggregation). For the
frequentist approaches, no pooling (with and without parametric or nonparametric
bootstrap) and complete pooling are implemented using
For the Bayesian approaches, no pooling, complete pooling, and three different
variants of partial pooling are implemented using
TreeBUGS <https://cran.r-project.org/package=TreeBUGS>. The main function is
fit_mpt() who performs the multiverse analysis in one call.
person("Henrik", "Singmann", role = c("aut", "cre"),
, person(c("Daniel", "W."), "Heck", email = "heck@uni-mannheim.de", role = c("aut"))
, person("Marius", "Barth", email = "marius.barth@uni-koeln.de", role = c("aut"))
, person("Frederik", "Aust", email = "frederik.aust@uni-koeln.de", role = c("ctb"),
Imports: parallel, magrittr, tidyr, dplyr, tibble, rlang, reshape2,
ggplot2, MPTinR, TreeBUGS, runjags, coda, purrr, broom, readr
Author: Henrik Singmann [aut, cre] (<https://orcid.org/0000-0002-4842-3657>),

ggplot2, MPTinR, TreeBUGS, runjags, coda, purrr, readr,

, person("Marius", "Barth", email = "marius.barth@uni-koeln.de", role = c("aut"),
ggplot2, MPTinR, TreeBUGS (>= 1.4.4), runjags, coda, purrr,

Title: Data Sets from Montgomery, Peck and Vining's Book
Description: These data sets are taken from the book Introduction
to Linear Regression Analysis (3rd ed), by the above authors.