A key diagnostic criterion of Somatic Symptom and related Disorders (SSD) comprises significant distress and excessive time-and-energy consuming thoughts, feelings, and behavior pertaining to somatic symptoms. This diagnostic criterion is lacking in central sensitivity syndromes (CSS), such as fibromyalgia, irritable bowel syndrome, and chronic fatigue syndrome. This strong emphasis on disturbed psychological processing of somatic symptoms, suggests that psychological flexibility is low in SDD.
View Article and Find Full Text PDFSome important research questions require the ability to find evidence for two conditions being practically equivalent. This is impossible to accomplish within the traditional frequentist null hypothesis significance testing framework; hence, other methodologies must be utilized. We explain and illustrate three approaches for finding evidence for equivalence: The frequentist two one-sided tests procedure, the Bayesian highest density interval region of practical equivalence procedure, and the Bayes factor interval null procedure.
View Article and Find Full Text PDFBehav Res Methods
October 2019
Signal detection theory (SDT) is used to quantify people's ability and bias in discriminating stimuli. The ability to detect a stimulus is often measured through confidence ratings. In SDT models, the use of confidence ratings necessitates the estimation of confidence category thresholds, a requirement that can easily result in models that are overly complex.
View Article and Find Full Text PDFBayesian parameter estimation and Bayesian hypothesis testing present attractive alternatives to classical inference using confidence intervals and p values. In part I of this series we outline ten prominent advantages of the Bayesian approach. Many of these advantages translate to concrete opportunities for pragmatic researchers.
View Article and Find Full Text PDFBayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and update this evidence as data come in, without the need to know the intention with which the data were collected. Despite these and other practical advantages, Bayesian hypothesis tests are still reported relatively rarely.
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