Multibridge: an R package to evaluate informed hypotheses in binomial and multinomial models.

Alexandra Sarafoglou, Frederik Aust, Maarten Marsman, František Bartoš, Eric-Jan Wagenmakers, Julia M Haaf

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Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Alexandra SarafoglouDepartment of Psychology, University of Amsterdam, PO Box 15906, 1001 NK Amsterdam, The Netherlands. alexandra.sarafoglou@gmail.com.

Frederik AustDepartment of Psychology, University of Amsterdam, PO Box 15906, 1001 NK Amsterdam, The Netherlands.

Maarten MarsmanDepartment of Psychology, University of Amsterdam, PO Box 15906, 1001 NK Amsterdam, The Netherlands.

František BartošDepartment of Psychology, University of Amsterdam, PO Box 15906, 1001 NK Amsterdam, The Netherlands.

Eric-Jan WagenmakersDepartment of Psychology, University of Amsterdam, PO Box 15906, 1001 NK Amsterdam, The Netherlands.

Julia M HaafDepartment of Psychology, University of Amsterdam, PO Box 15906, 1001 NK Amsterdam, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The multibridge R package allows a Bayesian evaluation of informed hypotheses [Formula: see text] applied to frequency data from an independent binomial or multinomial distribution. multibridge uses bridge sampling to efficiently compute Bayes factors for the following hypotheses concerning the latent category proportions 𝜃: (a) hypotheses that postulate equality constraints (e.g., 𝜃

Indexed as

Bayes TheoremHumansStatistical DistributionsBayes factorsBridge samplingInequality constraintsModel selectionSavage-Dickey density ratio

Identifiers

PMID37277644

DOI10.3758/s13428-022-02020-1

PMCPMC10700431

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