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:10.1037/0033295X.95.3.318>) models combining maximumlikelihood/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.rproject.org/package=MPTinR>. For the Bayesian approaches, no pooling, complete pooling, and three different variants of partial pooling are implemented using TreeBUGS <https://cran.rproject.org/package=TreeBUGS>. The main function is fit_mpt() which performs the multiverse analysis in one call.
Package details 


Maintainer  
License  GPL2 
Version  0.1 
URL  https://github.com/mptnetwork/MPTmultiverse.project 
Package repository  View on GitHub 
Installation 
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