Results 121 to 130 of about 34,617 (237)
Using Spreadsheets to Teach Signal Detection Theory
Spreadsheets in Education, 2014 Signal detection theory (SDT) is a mathematical framework for evaluating the performance of a detection system, which is broadly applicable across many academic and practical domains, including medicine, psychology, statistics and engineering.
Christopher R Fisher
doaj
To vary or not to vary: A flexible empirical Bayes factor for testing variance components
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
wiley +1 more source
Calibrating Bayesian inference
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu +2 more
wiley +1 more source
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Cognitive diagnostic models (CDMs) have become essential tools for providing fine‐grained information about individuals' mastery of cognitive skills. While prior reviews have emphasized statistical foundations and deep learning‐based developments, this article focuses on recent methodological innovations designed to address persistent ...
Chun Wang, Yale Quan, David Arthur
wiley +1 more source
Revisiting reliability and measurement precision: Towards a unified perspective
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract This article revisits the concepts of reliability and measurement precision across classical test theory (CTT), item response theory (IRT) and cognitive diagnosis models (CDMs), emphasizing their conceptual differences and proposing a unified framework.
Jimmy de la Torre +2 more
wiley +1 more source
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Sensitivity analysis for unmeasured confounders is essential for assessing the robustness of causal mediation conclusions. Most existing methods rely on parametric assumptions, which are ill‐suited for machine learning‐based estimators that are not tied to specific parametric models.
Xiao Liu, Cameron McCann
wiley +1 more source
Tobacco and alcohol use, fruit and vegetable consumption, physical activity habits, and participation in routine checkups and cancer screenings among adults aged 40 and older with and without chronic diseases: A cross-sectional study. [PDF]
Medicine (Baltimore)Yildirim-Ozturk EN, Uyar M.
europepmc +1 more source
When in Doubt, Tax More Progressively? Uncertainty and Progressive Income Taxation
International Economic Review, EarlyView.ABSTRACT We study the optimal income tax problem under parameter uncertainty about household preferences and wage dynamics. We derive conditions characterizing how such uncertainty affects optimal tax policy. To quantify the effect, we estimate a life‐cycle model using US data and a Bayesian approach.
Minsu Chang, Chunzan Wu
wiley +1 more source
From Inference to Ritual: Why Frequentist Statistics Became Hard to Understand and Teach in Medicine. [PDF]
J Eval Clin PractLega JC, Chevret S.
europepmc +1 more source
Using Bayesian tools to be a better frequentist
I am not a staunch advocate of Bayesian methods — I can totally see how for some questions a frequentist approach may provide more satisfactory answers. In this post, we'll explore how for a simple scenario (negative binomial regression with small sample
Martin Modrák
core +1 more source