plot.multiverseMPT

An object of class <code>multiverseMPT</code>.

Character. Which information should be plotted? Possible
values are
<code>"est"</code> for parameter estimates,
<code>"test_between"</code> for between-subjects comparisions,
<code>"gof1"</code> for overall goodness-of-fit statistics, and
<code>"gof2"</code> for group-wise goodness-of-fit statistics.

which

Logical. Indicates whether the plot should also be saved as a .pdf file.

save

Plot the results from a multiverse MPT analysis.

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
MPTinR <https://cran.r-project.org/package=MPTinR>.
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.

plot.multiverseMPT: Plot multiverseMPT

Description

Usage

Arguments