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Remiro-Azócar, Antonio; Heath, Anna; Baio, Gianluca – Research Synthesis Methods, 2022
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial differences in effect modifiers and limited patient-level data. MAIC is based on propensity score weighting, which is sensitive to poor covariate overlap and cannot extrapolate…
Descriptors: Patients, Medical Research, Comparative Analysis, Outcomes of Treatment
Kern, Holger L.; Stuart, Elizabeth A.; Hill, Jennifer; Green, Donald P. – Journal of Research on Educational Effectiveness, 2016
Randomized experiments are considered the gold standard for causal inference because they can provide unbiased estimates of treatment effects for the experimental participants. However, researchers and policymakers are often interested in using a specific experiment to inform decisions about other target populations. In education research,…
Descriptors: Educational Research, Generalization, Sampling, Participant Characteristics
Isaranuwatchai, Wanrudee; Brydges, Ryan; Carnahan, Heather; Backstein, David; Dubrowski, Adam – Advances in Health Sciences Education, 2014
While the ultimate goal of simulation training is to enhance learning, cost-effectiveness is a critical factor. Research that compares simulation training in terms of educational- and cost-effectiveness will lead to better-informed curricular decisions. Using previously published data we conducted a cost-effectiveness analysis of three…
Descriptors: Cost Effectiveness, Simulation, Medical Education, Training
Falk, Carl F.; Cai, Li – Journal of Educational Measurement, 2016
We present a logistic function of a monotonic polynomial with a lower asymptote, allowing additional flexibility beyond the three-parameter logistic model. We develop a maximum marginal likelihood-based approach to estimate the item parameters. The new item response model is demonstrated on math assessment data from a state, and a computationally…
Descriptors: Item Response Theory, Guessing (Tests), Mathematics Tests, Simulation
Sweet, Tracy M. – Journal of Educational and Behavioral Statistics, 2015
Social networks in education commonly involve some form of grouping, such as friendship cliques or teacher departments, and blockmodels are a type of statistical social network model that accommodate these grouping or blocks by assuming different within-group tie probabilities than between-group tie probabilities. We describe a class of models,…
Descriptors: Social Networks, Statistical Analysis, Probability, Models
Kopanidis, Foula Zografina; Shaw, Michael John – Education & Training, 2017
Purpose: Educational institutions are caught between increasing their offer rates and attracting and retaining those prospective students who are most suited to course completion. The purpose of this paper is to demonstrate the influence of demographic and psychological constructs on students' preferences when choosing to study in a particular…
Descriptors: Student Attitudes, Course Selection (Students), Preferences, Models
Sinharay, Sandip; Wan, Ping; Whitaker, Mike; Kim, Dong-In; Zhang, Litong; Choi, Seung W. – Journal of Educational Measurement, 2014
With an increase in the number of online tests, interruptions during testing due to unexpected technical issues seem unavoidable. For example, interruptions occurred during several recent state tests. When interruptions occur, it is important to determine the extent of their impact on the examinees' scores. There is a lack of research on this…
Descriptors: Computer Assisted Testing, Testing Problems, Scores, Regression (Statistics)
Klingler, Severin; Käser, Tanja; Solenthaler, Barbara; Gross, Markus – International Educational Data Mining Society, 2015
Modeling student knowledge is a fundamental task of an intelligent tutoring system. A popular approach for modeling the acquisition of knowledge is Bayesian Knowledge Tracing (BKT). Various extensions to the original BKT model have been proposed, among them two novel models that unify BKT and Item Response Theory (IRT). Latent Factor Knowledge…
Descriptors: Intelligent Tutoring Systems, Knowledge Level, Item Response Theory, Prediction
Vuolo, Mike – Sociological Methods & Research, 2017
Often in sociology, researchers are confronted with nonnormal variables whose joint distribution they wish to explore. Yet, assumptions of common measures of dependence can fail or estimating such dependence is computationally intensive. This article presents the copula method for modeling the joint distribution of two random variables, including…
Descriptors: Sociology, Research Methodology, Social Science Research, Models
Tipton, Elizabeth – Society for Research on Educational Effectiveness, 2014
Replication studies allow for making comparisons and generalizations regarding the effectiveness of an intervention across different populations, versions of a treatment, settings and contexts, and outcomes. One method for making these comparisons across many replication studies is through the use of meta-analysis. A recent innovation in…
Descriptors: Replication (Evaluation), Robustness (Statistics), Meta Analysis, Regression (Statistics)
Petersen, Janne; Bandeen-Roche, Karen; Budtz-Jorgensen, Esben; Larsen, Klaus Groes – Psychometrika, 2012
Latent class regression models relate covariates and latent constructs such as psychiatric disorders. Though full maximum likelihood estimation is available, estimation is often in three steps: (i) a latent class model is fitted without covariates; (ii) latent class scores are predicted; and (iii) the scores are regressed on covariates. We propose…
Descriptors: Computation, Prediction, Regression (Statistics), Maximum Likelihood Statistics
Benakli, Nadia; Kostadinov, Boyan; Satyanarayana, Ashwin; Singh, Satyanand – International Journal of Mathematical Education in Science and Technology, 2017
The goal of this paper is to promote computational thinking among mathematics, engineering, science and technology students, through hands-on computer experiments. These activities have the potential to empower students to learn, create and invent with technology, and they engage computational thinking through simulations, visualizations and data…
Descriptors: Calculus, Probability, Data Analysis, Computation
Keller, Bryan S. B.; Kim, Jee-Seon; Steiner, Peter M. – Society for Research on Educational Effectiveness, 2013
Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has…
Descriptors: Probability, Scores, Statistical Analysis, Statistical Bias
Lo, Yun-Jia – ProQuest LLC, 2012
In educational research, a randomized controlled trial is the best design to eliminate potential selection bias in a sample to support valid causal inferences, but it is not always possible in educational research because of financial, ethical, and logistical constrains. One alternative solution is use of the propensity score (PS) methods.…
Descriptors: Educational Research, Probability, Scores, Research Methodology
Kot, Felly Chiteng – Research in Higher Education, 2014
To enhance student success, many colleges and universities have expanded academic support services and programmatic interventions. One popular measure that has been recognized as critical to student success is academic advising. Many institutions have expanded advising by creating centralized units staffed with professional advisors who serve…
Descriptors: College Freshmen, Enrollment, Intervention, Academic Support Services
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