NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Researchers3
Laws, Policies, & Programs
Assessments and Surveys
Beck Depression Inventory1
What Works Clearinghouse Rating
Showing 1 to 15 of 44 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Cui, Zhongmin – Educational Measurement: Issues and Practice, 2021
Commonly used machine learning applications seem to relate to big data. This article provides a gentle review of machine learning and shows why machine learning can be applied to small data too. An example of applying machine learning to screen irregularity reports is presented. In the example, the support vector machine and multinomial naïve…
Descriptors: Artificial Intelligence, Man Machine Systems, Data, Bayesian Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
Hinterecker, Thomas; Knauff, Markus; Johnson-Laird, P. N. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2019
Individuals draw conclusions about possibilities from assertions that make no explicit reference to them. The model theory postulates that assertions such as disjunctions refer to possibilities. Hence, a disjunction of the sort, "A or B or both," where "A" and "B" are sensible clauses, yields mental models of an…
Descriptors: Logical Thinking, Abstract Reasoning, Inferences, Probability
Peer reviewed Peer reviewed
Direct linkDirect link
Hartshorne, Joshua K. – First Language, 2020
Ambridge argues that the existence of exemplar models for individual phenomena (words, inflection rules, etc.) suggests the feasibility of a unified, exemplars-everywhere model that eschews abstraction. The argument would be strengthened by a description of such a model. However, none is provided. I show that any attempt to do so would immediately…
Descriptors: Models, Language Acquisition, Language Processing, Bayesian Statistics
Peer reviewed Peer reviewed
Direct linkDirect link
Hanushek, Eric A. – Measurement: Interdisciplinary Research and Perspectives, 2016
E. A. Hanushek points out in this commentary that applied researchers in education have only recently begun to appreciate the value of international assessments, even though there are now 50 years of experience with these. Until recently, these assessments have been stand-alone surveys that have not been linked, and analysis has largely focused on…
Descriptors: Reading Tests, Bayesian Statistics, International Assessment, Educational Trends
Peer reviewed Peer reviewed
Direct linkDirect link
Storm, Lance; Tressoldi, Patrizio E.; Utts, Jessica – Psychological Bulletin, 2013
Rouder, Morey, and Province (2013) stated that (a) the evidence-based case for psi in Storm, Tressoldi, and Di Risio's (2010) meta-analysis is supported only by a number of studies that used manual randomization, and (b) when these studies are excluded so that only investigations using automatic randomization are evaluated (and some additional…
Descriptors: Meta Analysis, Evidence, Bayesian Statistics, Investigations
Peer reviewed Peer reviewed
Direct linkDirect link
Rouder, Jeffrey N.; Morey, Richard D.; Province, Jordan M. – Psychological Bulletin, 2013
Psi phenomena, such as mental telepathy, precognition, and clairvoyance, have garnered much recent attention. We reassess the evidence for psi effects from Storm, Tressoldi, and Di Risio's (2010) meta-analysis. Our analysis differs from Storm et al.'s in that we rely on Bayes factors, a Bayesian approach for stating the evidence from data for…
Descriptors: Evidence, Bayesian Statistics, Meta Analysis, Cognitive Ability
Peer reviewed Peer reviewed
Direct linkDirect link
Bowers, Jeffrey S.; Davis, Colin J. – Psychological Bulletin, 2012
Griffiths, Chater, Norris, and Pouget (2012) argue that we have misunderstood the Bayesian approach. In their view, it is rarely the case that researchers are making claims that performance in a given task is near optimal, and few, if any, researchers adopt the theoretical Bayesian perspective according to which the mind or brain is actually…
Descriptors: Bayesian Statistics, Psychology, Brain, Theories
Peer reviewed Peer reviewed
Direct linkDirect link
Wills, Andy J.; Pothos, Emmanuel M. – Psychological Bulletin, 2012
Vanpaemel and Lee (2012) argued, and we agree, that the comparison of formal models can be facilitated by Bayesian methods. However, Bayesian methods neither precede nor supplant our proposals (Wills & Pothos, 2012), as Bayesian methods can be applied both to our proposals and to their polar opposites. Furthermore, the use of Bayesian methods to…
Descriptors: Classification, Bayesian Statistics, Models, Comparative Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Vanpaemel, Wolf; Lee, Michael D. – Psychological Bulletin, 2012
Wills and Pothos (2012) reviewed approaches to evaluating formal models of categorization, raising a series of worthwhile issues, challenges, and goals. Unfortunately, in discussing these issues and proposing solutions, Wills and Pothos (2012) did not consider Bayesian methods in any detail. This means not only that their review excludes a major…
Descriptors: Classification, Program Evaluation, Bayesian Statistics, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Edwards, Michael C. – Measurement: Interdisciplinary Research and Perspectives, 2013
This author has had the privilege of knowing Professor Maydeu-Olivares for almost a decade and although their paths cross only occasionally, such instances were always enjoyable and enlightening. Edwards states that Maydeu-Olivares' target article for this issue, ("Goodness-of-Fit Assessment of Item Response Theory Models") provides…
Descriptors: Goodness of Fit, Item Response Theory, Models, Factor Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Rossman, Allan; Utts, Jessica – Journal of Statistics Education, 2014
This article offers a transcript of author Allan Rossman's interview with Jessica Utts, Professor and Chair of Statistics at the University of California-Irvine. Utts is also a Fellow of the American Statistical Association and a recipient of a Founders Award from ASA. Additionally, she has been elected as President of ASA for the year 2016. The…
Descriptors: Interviews, Statistics, College Faculty, College Mathematics
Peer reviewed Peer reviewed
Direct linkDirect link
Ahern, David C.; Bridges, Ana J.; Faust, David – Journal of Child Sexual Abuse, 2012
Our series of three chapters (Faust, Bridges, & Ahern, 2009a, 2009b; Bridges, Faust, & Ahern, 2009) on the methodology of identifying sexually abused children elicited a number of comments, both supportive and critical. The criticisms appear related to three primary issues or apparent misconceptions of our work, perhaps due in part to incomplete…
Descriptors: Child Abuse, Misconceptions, Sexual Abuse, Identification
Peer reviewed Peer reviewed
Direct linkDirect link
Jordan, Pascal; Spiess, Martin – Psychometrika, 2012
Maximum likelihood and Bayesian ability estimation in multidimensional item response models can lead to paradoxical results as proven by Hooker, Finkelman, and Schwartzman ("Psychometrika" 74(3): 419-442, 2009): Changing a correct response on one item into an incorrect response may produce a higher ability estimate in one dimension.…
Descriptors: Item Response Theory, Statistical Analysis, Factor Analysis, Generalization
Peer reviewed Peer reviewed
Direct linkDirect link
Jo, Booil; Stuart, Elizabeth A. – Journal of Research on Educational Effectiveness, 2012
The authors thank Dr. Lindsay Page for providing a nice illustration of the use of the principal stratification framework to define causal effects, and a Bayesian model for effect estimation. They hope that her well-written article will help expose education researchers to these concepts and methods, and move the field of mediation analysis in…
Descriptors: Bayesian Statistics, Educational Experiments, Educational Research, Observation
Peer reviewed Peer reviewed
Direct linkDirect link
Drummond, Gordon B.; Vowler, Sarah L. – Advances in Physiology Education, 2012
Most biological scientists conduct experiments to look for effects, and test the results statistically. One of the commonly used test is Student's t test. However, this test concentrates on a very limited question. The authors assume that there is no effect in the experiment, and then estimate the possibility that they could have obtained these…
Descriptors: Statistical Significance, Scientists, Tests, Biology
Previous Page | Next Page »
Pages: 1  |  2  |  3