The power prior has been widely used in many applications covering a large number of disciplines. The power prior is intended to be an informative prior constructed from historical data. It has been used in clinical trials, genetics, health care, psychology, environmental health, engineering, economics, and business. It has also been applied for a wide variety of models and settings, both in the experimental design and analysis contexts. In this review article, we give an A-to-Z exposition of the power prior and its applications to date. We review its theoretical properties, variations in its formulation, statistical contexts for which it has been used, applications, and its advantages over other informative priors. We review models for which it has been used, including generalized linear models, survival models, and random effects models. Statistical areas where the power prior has been used include model selection, experimental design, hierarchical modeling, and conjugate priors. Frequentist properties of power priors in posterior inference are established, and a simulation study is conducted to further examine the empirical performance of the posterior estimates with power priors. Real data analyses are given illustrating the power prior as well as the use of the power prior in the Bayesian design of clinical trials.
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http://dx.doi.org/10.1002/sim.6728 | DOI Listing |
J Med Internet Res
January 2025
Institute of Medical Teaching and Medical Education Research, University Hospital Würzburg, Würzburg, Germany.
Background: Objective structured clinical examinations (OSCEs) are a widely recognized and accepted method to assess clinical competencies but are often resource-intensive.
Objective: This study aimed to evaluate the feasibility and effectiveness of a virtual reality (VR)-based station (VRS) compared with a traditional physical station (PHS) in an already established curricular OSCE.
Methods: Fifth-year medical students participated in an OSCE consisting of 10 stations.
Nat Genet
January 2025
Department of Statistics, University of Oxford, Oxford, UK.
The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration.
View Article and Find Full Text PDFAtten Percept Psychophys
January 2025
Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, Van Der Boechorststraat 7, 1081 BT, Amsterdam, The Netherlands.
In previous studies, it was established that individuals can implicitly learn spatiotemporal regularities related to how the distribution of target locations unfolds across the time course of a single trial. However, these regularities were tied to the appearance of salient targets that are known to capture attention in a bottom-up way. The current study investigated whether the saliency of target is necessary for this type of learning to occur.
View Article and Find Full Text PDFGait Posture
December 2024
Department of Physical Therapy and Rehabilitation Science, Carver College of Medicine, University of Iowa, Iowa City, IA, USA.
Background: Carbon fiber custom dynamic orthoses have been used to improve gait mechanics after lower limb trauma in military service members, with the goal of restoring function and improving outcomes. However, the effects of commercially available carbon fiber orthoses available to civilians on lower extremity joint kinetics and kinematics are poorly understood.
Research Question: The aim of this study was to examine the effect of two commercially available orthoses on lower extremity kinematics and kinetics in individuals with lower limb trauma.
J Med Internet Res
January 2025
College of Nursing, University of Nebraska Medical Center, Omaha, NE, United States.
Background: The known and established benefits of exercise in patients with heart failure (HF) are often hampered by low exercise adherence. Mobile health (mHealth) technology provides opportunities to overcome barriers to exercise adherence in this population.
Objective: This systematic review builds on prior research to (1) describe study characteristics of mHealth interventions for exercise adherence in HF including details of sample demographics, sample sizes, exercise programs, and theoretical frameworks; (2) summarize types of mHealth technology used to improve exercise adherence in patients with HF; (3) highlight how the term "adherence" was defined and how it was measured across mHealth studies and adherence achieved; and (4) highlight the effect of age, sex, race, New York Heart Association (NYHA) functional classification, and HF etiology (systolic vs diastolic) on exercise adherence.
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