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Uhlmann, Lorenz; Jensen, Katrin; Kieser, Meinhard – Research Synthesis Methods, 2017
Network meta-analysis is becoming a common approach to combine direct and indirect comparisons of several treatment arms. In recent research, there have been various developments and extensions of the standard methodology. Simultaneously, cluster randomized trials are experiencing an increased popularity, especially in the field of health services…
Descriptors: Bayesian Statistics, Network Analysis, Meta Analysis, Randomized Controlled Trials
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Hsu, Anne S.; Horng, Andy; Griffiths, Thomas L.; Chater, Nick – Cognitive Science, 2017
Identifying patterns in the world requires noticing not only unusual occurrences, but also unusual absences. We examined how people learn from absences, manipulating the extent to which an absence is expected. People can make two types of inferences from the absence of an event: either the event is possible but has not yet occurred, or the event…
Descriptors: Statistical Inference, Bayesian Statistics, Evidence, Prediction
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Marmolejo-Ramos, Fernando; Cousineau, Denis – Educational and Psychological Measurement, 2017
The number of articles showing dissatisfaction with the null hypothesis statistical testing (NHST) framework has been progressively increasing over the years. Alternatives to NHST have been proposed and the Bayesian approach seems to have achieved the highest amount of visibility. In this last part of the special issue, a few alternative…
Descriptors: Hypothesis Testing, Bayesian Statistics, Evaluation Methods, Statistical Inference
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Pedder, Hugo; Dias, Sofia; Bennetts, Margherita; Boucher, Martin; Welton, Nicky J. – Research Synthesis Methods, 2019
Background: Model-based meta-analysis (MBMA) is increasingly used to inform drug-development decisions by synthesising results from multiple studies to estimate treatment, dose-response, and time-course characteristics. Network meta-analysis (NMA) is used in Health Technology Appraisals for simultaneously comparing effects of multiple treatments,…
Descriptors: Meta Analysis, Guidelines, Drug Therapy, Decision Making
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Zax, Alexandra; Williams, Katherine; Patalano, Andrea L.; Slusser, Emily; Cordes, Sara; Barth, Hilary – Journal of Cognition and Development, 2019
Similar estimation biases appear in a wide range of quantitative judgments, across many tasks and domains. Often, these biases (those that occur, for example, when adults or children indicate remembered locations of objects in bounded spaces) are believed to provide evidence of Bayesian or rational cognitive processing, and are explained in terms…
Descriptors: Undergraduate Students, Elementary School Students, Bayesian Statistics, Cognitive Processes
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Önen, Emine – Universal Journal of Educational Research, 2019
This simulation study was conducted to compare the performances of Frequentist and Bayesian approaches in the context of power to detect model misspecification in terms of omitted cross-loading in CFA models with respect to the several variables (number of omitted cross-loading, magnitude of main loading, number of factors, number of indicators…
Descriptors: Factor Analysis, Bayesian Statistics, Comparative Analysis, Statistical Analysis
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Oleson, Jacob J.; Brown, Grant D.; McCreery, Ryan – Journal of Speech, Language, and Hearing Research, 2019
Purpose: Scientists in the speech, language, and hearing sciences rely on statistical analyses to help reveal complex relationships and patterns in the data collected from their research studies. However, data from studies in the fields of communication sciences and disorders rarely conform to the underlying assumptions of many traditional…
Descriptors: Speech Language Pathology, Data Collection, Interpersonal Communication, Communication Problems
Lee, Steven Fong-yi – ProQuest LLC, 2019
In this dissertation I argue that truth-conditional semantics for vague predicates, combined with a Bayesian account of statistical inference incorporating knowledge of truth-conditions of utterances, generates false predictions regarding negations and metalinguistic inference. I thus propose a fundamentally probabilistic semantics for vagueness…
Descriptors: Semantics, Bayesian Statistics, Metalinguistics, Language Usage
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Carly Oddleifson; Stephen Kilgus; David A. Klingbeil; Alexander D. Latham; Jessica S. Kim; Ishan N. Vengurlekar – Grantee Submission, 2025
The purpose of this study was to conduct a conceptual replication of Pendergast et al.'s (2018) study that examined the diagnostic accuracy of a nomogram procedure, also known as a naive Bayesian approach. The specific naive Bayesian approach combined academic and social-emotional and behavioral (SEB) screening data to predict student performance…
Descriptors: Bayesian Statistics, Accuracy, Social Emotional Learning, Diagnostic Tests
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
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Ning, Ling; Luo, Wen – Journal of Experimental Education, 2018
Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…
Descriptors: Statistical Analysis, Models, Classification, Comparative Analysis
Wang, Chun; Xu, Gongjun; Shang, Zhuoran; Kuncel, Nathan – Journal of Educational and Behavioral Statistics, 2018
The modern web-based technology greatly popularizes computer-administered testing, also known as online testing. When these online tests are administered continuously within a certain "testing window," many items are likely to be exposed and compromised, posing a type of test security concern. In addition, if the testing time is limited,…
Descriptors: Computer Assisted Testing, Cheating, Guessing (Tests), Item Response Theory
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Sinharay, Sandip – Measurement: Interdisciplinary Research and Perspectives, 2018
Producers and consumers of test scores are increasingly concerned about fraudulent behavior before and during the test. There exist several statistical or psychometric methods for detecting fraudulent behavior on tests. This paper provides a review of the Bayesian approaches among them. Four hitherto-unpublished real data examples are provided to…
Descriptors: Ethics, Cheating, Student Behavior, Bayesian Statistics
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Nicenboim, Bruno; Vasishth, Shravan; Engelmann, Felix; Suckow, Katja – Cognitive Science, 2018
Given the replication crisis in cognitive science, it is important to consider what researchers need to do in order to report results that are reliable. We consider three changes in current practice that have the potential to deliver more realistic and robust claims. First, the planned experiment should be divided into two stages, an exploratory…
Descriptors: Sentences, Case Studies, Cognitive Science, Psycholinguistics
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Peralta, Montserrat; Alarcon, Rosa; Pichara, Karim E.; Mery, Tomas; Cano, Felipe; Bozo, Jorge – IEEE Transactions on Learning Technologies, 2018
Educational resources can be easily found on the Web. Most search engines base their algorithms on a resource's text or popularity, requiring teachers to navigate the results until they find an appropriate resource. This makes searching for resources a tedious and cumbersome task. Specialized repositories contain resources that are annotated with…
Descriptors: Educational Resources, Metadata, Foreign Countries, Bayesian Statistics
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