TY - JOUR
T1 - Power Analysis, p Values, and Bayesian Techniques
T2 - How Bayesian Techniques Can Be Used in HRD Literature
AU - Baker, Rose
AU - Hirudayaraj, Malar
N1 - Funding Information:
This study was funded by the Netherlands Organisation for Health Research and Development (project number 113303005 to WEV), and the Sherman Foundation (to WEV). We thank the patients for contributing to this study and their families for the ongoing support. The centres in Rotterdam, Berlin, Paris, Prague, Angers, and Toulouse are part of the European Reference Network on rare endocrine conditions (Endo-ERN). The centre in Rome is part of the European Reference Network for Rare Neurological Disorders (ERN RND). The centre in Cambridge (UK) is supported by the Wellcome Trust and the National Institute of Health Research Biomedical Research Centre.
Funding Information:
WEV reports grants from Netherlands Organisation for Health Research and Development and from the Sherman Foundation. The Erasmus Medical Centre (Rotterdam, Netherlands), which employs SG, FSvG, IMvB, MD, MMvdK, CAU, MCYdW, and WEV might receive royalties from Rare Thyroid Therapeutics (the manufacturer of Triac) in the future, dependent on any future commercialisation. None of the authors will benefit personally from any royalties. Rare Thyroid Therapeutics had no influence on the conduct or analysis of this study. DC reports grants from BioMarine, UCB, and A&D Pharma. MCYdW reports consultation fees from Hoffmann- La Roche and Ionis, paid to the Erasmus Medical Center. All other authors declare no competing interests.
Publisher Copyright:
© The Author(s) 2019.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - The Problem: Researchers have described challenges and problems in reporting research that uses only p values and power to make decisions to reject the null hypothesis. Confusion about how to interpret null hypothesis statistical tests has resulted from mixed information presented in statistics articles and textbooks. The Solution: Combining evidence from data with initial beliefs, Bayesian inference techniques help to provide uncontroversial support of a null hypothesis or alternative hypothesis. An overview of the limitations associated with only using p values and power to make decisions to reject or retain the null hypothesis are presented. Analyses across multiple studies with common parameters can be pooled using Bayesian techniques as a means for conducting meta-analysis. Examples using Bayesian techniques are given. The Stakeholders: When designing a research study, researchers often use external elements and likelihood to make powerful inferences using Bayesian techniques. Those performing research in populations requiring sampling.
AB - The Problem: Researchers have described challenges and problems in reporting research that uses only p values and power to make decisions to reject the null hypothesis. Confusion about how to interpret null hypothesis statistical tests has resulted from mixed information presented in statistics articles and textbooks. The Solution: Combining evidence from data with initial beliefs, Bayesian inference techniques help to provide uncontroversial support of a null hypothesis or alternative hypothesis. An overview of the limitations associated with only using p values and power to make decisions to reject or retain the null hypothesis are presented. Analyses across multiple studies with common parameters can be pooled using Bayesian techniques as a means for conducting meta-analysis. Examples using Bayesian techniques are given. The Stakeholders: When designing a research study, researchers often use external elements and likelihood to make powerful inferences using Bayesian techniques. Those performing research in populations requiring sampling.
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U2 - 10.1177/1523422319870565
DO - 10.1177/1523422319870565
M3 - Article
AN - SCOPUS:85072126461
SN - 1523-4223
VL - 21
SP - 438
EP - 465
JO - Advances in Developing Human Resources
JF - Advances in Developing Human Resources
IS - 4
ER -