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Bayesian evaluation of informative hypotheses in cluster-randomized trials
Researchers often have informative hypotheses in mind when comparing means across treatment groups, such as H(1) : μ(A) < μ(B) < μ(C) and H(2) : μ(B) < μ(A) < μ(C), and want to compare these hypotheses to each other directly. This can be done by means of Bayesian inference. This article...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer US
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6420439/ https://www.ncbi.nlm.nih.gov/pubmed/30350025 http://dx.doi.org/10.3758/s13428-018-1149-x |