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Sample-size determination for the Bayesian t test and Welch’s test using the approximate adjusted fractional Bayes factor
When two independent means μ(1) and μ(2) are compared, H(0) : μ(1) = μ(2), H(1) : μ(1)≠μ(2), and H(2) : μ(1) > μ(2) are the hypotheses of interest. This paper introduces the R package SSDbain, which can be used to determine the sample size needed to evaluate these hypotheses using the approximate...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880954/ https://www.ncbi.nlm.nih.gov/pubmed/32632740 http://dx.doi.org/10.3758/s13428-020-01408-1 |
Sumario: | When two independent means μ(1) and μ(2) are compared, H(0) : μ(1) = μ(2), H(1) : μ(1)≠μ(2), and H(2) : μ(1) > μ(2) are the hypotheses of interest. This paper introduces the R package SSDbain, which can be used to determine the sample size needed to evaluate these hypotheses using the approximate adjusted fractional Bayes factor (AAFBF) implemented in the R package bain. Both the Bayesian t test and the Bayesian Welch’s test are available in this R package. The sample size required will be calculated such that the probability that the Bayes factor is larger than a threshold value is at least η if either the null or alternative hypothesis is true. Using the R package SSDbain and/or the tables provided in this paper, psychological researchers can easily determine the required sample size for their experiments. |
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