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A tutorial on Bayesian single-test reliability analysis with JASP
The current practice of reliability analysis is both uniform and troublesome: most reports consider only Cronbach’s α, and almost all reports focus exclusively on a point estimate, disregarding the impact of sampling error. In an attempt to improve the status quo we have implemented Bayesian estimat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10126026/ https://www.ncbi.nlm.nih.gov/pubmed/35581436 http://dx.doi.org/10.3758/s13428-021-01778-0 |
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author | Pfadt, Julius M. Bergh, Don van den Sijtsma, Klaas Wagenmakers, Eric-Jan |
author_facet | Pfadt, Julius M. Bergh, Don van den Sijtsma, Klaas Wagenmakers, Eric-Jan |
author_sort | Pfadt, Julius M. |
collection | PubMed |
description | The current practice of reliability analysis is both uniform and troublesome: most reports consider only Cronbach’s α, and almost all reports focus exclusively on a point estimate, disregarding the impact of sampling error. In an attempt to improve the status quo we have implemented Bayesian estimation routines for five popular single-test reliability coefficients in the open-source statistical software program JASP. Using JASP, researchers can easily obtain Bayesian credible intervals to indicate a range of plausible values and thereby quantify the precision of the point estimate. In addition, researchers may use the posterior distribution of the reliability coefficients to address practically relevant questions such as “What is the probability that the reliability of my test is larger than a threshold value of .80?”. In this tutorial article, we outline how to conduct a Bayesian reliability analysis in JASP and correctly interpret the results. By making available a computationally complex procedure in an easy-to-use software package, we hope to motivate researchers to include uncertainty estimates whenever reporting the results of a single-test reliability analysis. |
format | Online Article Text |
id | pubmed-10126026 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-101260262023-04-26 A tutorial on Bayesian single-test reliability analysis with JASP Pfadt, Julius M. Bergh, Don van den Sijtsma, Klaas Wagenmakers, Eric-Jan Behav Res Methods Article The current practice of reliability analysis is both uniform and troublesome: most reports consider only Cronbach’s α, and almost all reports focus exclusively on a point estimate, disregarding the impact of sampling error. In an attempt to improve the status quo we have implemented Bayesian estimation routines for five popular single-test reliability coefficients in the open-source statistical software program JASP. Using JASP, researchers can easily obtain Bayesian credible intervals to indicate a range of plausible values and thereby quantify the precision of the point estimate. In addition, researchers may use the posterior distribution of the reliability coefficients to address practically relevant questions such as “What is the probability that the reliability of my test is larger than a threshold value of .80?”. In this tutorial article, we outline how to conduct a Bayesian reliability analysis in JASP and correctly interpret the results. By making available a computationally complex procedure in an easy-to-use software package, we hope to motivate researchers to include uncertainty estimates whenever reporting the results of a single-test reliability analysis. Springer US 2022-05-17 2023 /pmc/articles/PMC10126026/ /pubmed/35581436 http://dx.doi.org/10.3758/s13428-021-01778-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pfadt, Julius M. Bergh, Don van den Sijtsma, Klaas Wagenmakers, Eric-Jan A tutorial on Bayesian single-test reliability analysis with JASP |
title | A tutorial on Bayesian single-test reliability analysis with JASP |
title_full | A tutorial on Bayesian single-test reliability analysis with JASP |
title_fullStr | A tutorial on Bayesian single-test reliability analysis with JASP |
title_full_unstemmed | A tutorial on Bayesian single-test reliability analysis with JASP |
title_short | A tutorial on Bayesian single-test reliability analysis with JASP |
title_sort | tutorial on bayesian single-test reliability analysis with jasp |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10126026/ https://www.ncbi.nlm.nih.gov/pubmed/35581436 http://dx.doi.org/10.3758/s13428-021-01778-0 |
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