get_pb_output

<p>Helper function for creating parametric-bootstrap confidence intervals.</p>

internal


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.

get_pb_output: Parametric Bootstrap for MPT

Description

Usage

Arguments