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www.fharrell.com | ||
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fharrell.com
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| | | | | This is the story of what influenced me to become a Bayesian statistician after being trained as a classical frequentist statistician, and practicing only that mode of statistics for many years. | |
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hbiostat.org
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| | | | | In this article I provide much more extensive simulations showing the near perfect agreement between the odds ratio (OR) from a proportional odds (PO) model, and the Wilcoxon two-sample test statistic. The agreement is studied by degree of violation of the PO assumption and by the sample size. A refinement in the conversion formula between the OR and the Wilcoxon statistic scaled to 0-1 (corcordance probability) is provided. | |
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alexanderetz.com
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| | | | | [This post has been updated and turned into a paper to be published in AMPPS] Much of the discussion in psychology surrounding Bayesian inference focuses on priors. Should we embrace priors, or should we be skeptical? When are Bayesian methods sensitive to specification of the prior, and when do the data effectively overwhelm it? Should... | |
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simkovic.github.io
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| | | [AI summary] This post discusses the limitations of using raw score differences in ordinal data analysis, particularly when dealing with ceiling effects. The author demonstrates that raw score differences can be biased towards zero and have reduced precision in boundary regions. They advocate for using logit-based models to accurately estimate treatment effects while accounting for ordinal data structure and ceiling effects. The post includes simulations showing how ceiling effects can reduce the detectability of true effects and highlights the importance of using appropriate statistical models to avoid biased conclusions. | ||
