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Liu, Haiyan; Zhang, Zhiyong; Grimm, Kevin J. – Grantee Submission, 2016
Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due…
Descriptors: Bayesian Statistics, Computation, Statistical Analysis, Growth Models
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McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…
Descriptors: Probability, Age Differences, Children, Intervention
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Kaplan, David; Chen, Jianshen – Society for Research on Educational Effectiveness, 2013
The purpose of this study is to explore Bayesian model averaging in the propensity score context. Previous research on Bayesian propensity score analysis does not take into account model uncertainty. In this regard, an internally consistent Bayesian framework for model building and estimation must also account for model uncertainty. The…
Descriptors: Bayesian Statistics, Models, Probability, Monte Carlo Methods
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Lyon, Thomas D.; Ahern, Elizabeth C.; Scurich, Nicholas – Journal of Child Sexual Abuse, 2012
We describe a Bayesian approach to evaluating children's abuse disclosures and review research demonstrating that children's disclosure of genital touch can be highly probative of sexual abuse, with the probative value depending on disclosure spontaneity and children's age. We discuss how some commentators understate the probative value of…
Descriptors: Sexual Abuse, Interviews, Probability, Bayesian Statistics
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Lee, Jihyun; Corter, James E. – Applied Psychological Measurement, 2011
Diagnosis of misconceptions or "bugs" in procedural skills is difficult because of their unstable nature. This study addresses this problem by proposing and evaluating a probability-based approach to the diagnosis of bugs in children's multicolumn subtraction performance using Bayesian networks. This approach assumes a causal network relating…
Descriptors: Misconceptions, Probability, Children, Subtraction
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Rock, Donald A. – ETS Research Report Series, 2012
This paper provides a history of ETS's role in developing assessment instruments and psychometric procedures for measuring change in large-scale national assessments funded by the Longitudinal Studies branch of the National Center for Education Statistics. It documents the innovations developed during more than 30 years of working with…
Descriptors: Models, Educational Change, Longitudinal Studies, Educational Development
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Zhu, Liqi; Gigerenzer, Gerd – Cognition, 2006
Can children reason the Bayesian way? We argue that the answer to this question depends on how numbers are represented, because a representation can do part of the computation. We test, for the first time, whether Bayesian reasoning can be elicited in children by means of natural frequencies. We show that when information was presented to fourth,…
Descriptors: Mental Computation, Probability, Bayesian Statistics, Intermediate Grades