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Lee, Soo; Suh, Youngsuk – Journal of Educational Measurement, 2018
Lord's Wald test for differential item functioning (DIF) has not been studied extensively in the context of the multidimensional item response theory (MIRT) framework. In this article, Lord's Wald test was implemented using two estimation approaches, marginal maximum likelihood estimation and Bayesian Markov chain Monte Carlo estimation, to detect…
Descriptors: Item Response Theory, Sample Size, Models, Error of Measurement
Anglim, Jeromy; Wynton, Sarah K. A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, Learning, Statistical Analysis
Jamil, Tahira; Marsman, Maarten; Ly, Alexander; Morey, Richard D.; Wagenmakers, Eric-Jan – Educational and Psychological Measurement, 2017
In 1881, Donald MacAlister posed a problem in the "Educational Times" that remains relevant today. The problem centers on the statistical evidence for the effectiveness of a treatment based on a comparison between two proportions. A brief historical sketch is followed by a discussion of two default Bayesian solutions, one based on a…
Descriptors: Bayesian Statistics, Evidence, Comparative Analysis, Problem Solving
Kim, Weon H. – ProQuest LLC, 2017
The purpose of the present study is to apply the item response theory (IRT) and testlet response theory (TRT) models to a reading comprehension test. This study applied the TRT models and the traditional IRT model to a seventh-grade reading comprehension test (n = 8,815) with eight testlets. These three models were compared to determine the best…
Descriptors: Item Response Theory, Test Items, Correlation, Reading Tests
Trolian, Teniell L.; An, Brian P.; Pascarella, Ernest T. – Journal of College Student Development, 2016
For this study we considered the influence of binge drinking behavior in college on students' critical thinking gains. Findings suggest that binge drinking has a negative influence on students' critical thinking gains over 4 years of college and that this effect was driven by students with the lowest levels of precollege critical thinking. In both…
Descriptors: Alcohol Abuse, Drinking, Alcoholism, Critical Thinking
Pan, Yilin – Society for Research on Educational Effectiveness, 2016
Given the necessity to bridge the gap between what happened and what is likely to happen, this paper aims to explore how to apply Bayesian inference to cost-effectiveness analysis so as to capture the uncertainty of a ratio-type efficiency measure. The first part of the paper summarizes the characteristics of the evaluation data that are commonly…
Descriptors: Resource Allocation, Cost Effectiveness, Bayesian Statistics, Statistical Analysis
Nelson, Peter M.; Van Norman, Ethan R.; Klingbeil, Dave A.; Parker, David C. – Psychology in the Schools, 2017
Although extensive research exists on the use of curriculum-based measures for progress monitoring, little is known about using computer adaptive tests (CATs) for progress-monitoring purposes. The purpose of this study was to evaluate the impact of the frequency of data collection on individual and group growth estimates using a CAT. Data were…
Descriptors: Progress Monitoring, Computer Assisted Testing, Data Collection, Scheduling
Kim, Sooyeon; Moses, Tim; Yoo, Hanwook – Journal of Educational Measurement, 2015
This inquiry is an investigation of item response theory (IRT) proficiency estimators' accuracy under multistage testing (MST). We chose a two-stage MST design that includes four modules (one at Stage 1, three at Stage 2) and three difficulty paths (low, middle, high). We assembled various two-stage MST panels (i.e., forms) by manipulating two…
Descriptors: Comparative Analysis, Item Response Theory, Computation, Accuracy
Oh, Hanna; Beck, Jeffrey M.; Zhu, Pingping; Sommer, Marc A.; Ferrari, Silvia; Egner, Tobias – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Much of our real-life decision making is bounded by uncertain information, limitations in cognitive resources, and a lack of time to allocate to the decision process. It is thought that humans overcome these limitations through "satisficing," fast but "good-enough" heuristic decision making that prioritizes some sources of…
Descriptors: Decision Making, Cues, Cognitive Processes, Time
Schmid, Christopher H.; Trikalinos, Thomas A.; Olkin, Ingram – Research Synthesis Methods, 2014
We develop a Bayesian multinomial network meta-analysis model for unordered (nominal) categorical outcomes that allows for partially observed data in which exact event counts may not be known for each category. This model properly accounts for correlations of counts in mutually exclusive categories and enables proper comparison and ranking of…
Descriptors: Bayesian Statistics, Correlation, Comparative Analysis, Meta Analysis
Yamaguchi, Yusuke; Sakamoto, Wataru; Goto, Masashi; Staessen, Jan A.; Wang, Jiguang; Gueyffier, Francois; Riley, Richard D. – Research Synthesis Methods, 2014
When some trials provide individual patient data (IPD) and the others provide only aggregate data (AD), meta-analysis methods for combining IPD and AD are required. We propose a method that reconstructs the missing IPD for AD trials by a Bayesian sampling procedure and then applies an IPD meta-analysis model to the mixture of simulated IPD and…
Descriptors: Meta Analysis, Patients, Bayesian Statistics, Comparative Analysis
Choi, In-Hee; Wilson, Mark – Educational and Psychological Measurement, 2015
An essential feature of the linear logistic test model (LLTM) is that item difficulties are explained using item design properties. By taking advantage of this explanatory aspect of the LLTM, in a mixture extension of the LLTM, the meaning of latent classes is specified by how item properties affect item difficulties within each class. To improve…
Descriptors: Classification, Test Items, Difficulty Level, Statistical Analysis
Dawson, Christi L.; Hennessey, Maeghan N.; Higley, Kelli – International Journal of Higher Education, 2016
This study investigated the perceptions of epistemic justification of students in two disparate domains of study to determine if any similarities and differences in their methods of justification exist. Two samples of students, or a total of 513 undergraduates from educational psychology (n = 193) and biology (n = 320) courses, completed a…
Descriptors: Student Attitudes, Biology, Teaching Methods, Educational Psychology
Nosofsky, Robert M.; Donkin, Chris – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
We report an experiment designed to provide a qualitative contrast between knowledge-limited versions of mixed-state and variable-resources (VR) models of visual change detection. The key data pattern is that observers often respond "same" on big-change trials, while simultaneously being able to discriminate between same and small-change…
Descriptors: Short Term Memory, Probability, Models, Prediction
Premlatha, K. R.; Dharani, B.; Geetha, T. V. – Interactive Learning Environments, 2016
E-learning allows learners individually to learn "anywhere, anytime" and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to…
Descriptors: Electronic Learning, Profiles, Automation, Classification

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