Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 5 |
Since 2006 (last 20 years) | 6 |
Descriptor
Source
Society for Research on… | 2 |
Educational and Psychological… | 1 |
Journal of Policy Analysis… | 1 |
Journal of Research on… | 1 |
RAND Corporation | 1 |
Author
Altindag, Onur | 1 |
Crockett, Sean | 1 |
Hallberg, Kelly | 1 |
Jaeger, David A. | 1 |
Joyce, Ted | 1 |
Kamata, Akihito | 1 |
Li, Ji | 1 |
Liang, Xinya | 1 |
O'Connell, Stephen D. | 1 |
Opper, Isaac M. | 1 |
Pustejovsky, James E. | 1 |
More ▼ |
Publication Type
Reports - Research | 5 |
Journal Articles | 3 |
Reports - Evaluative | 1 |
Education Level
Higher Education | 1 |
Postsecondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Liang, Xinya; Kamata, Akihito; Li, Ji – Educational and Psychological Measurement, 2020
One important issue in Bayesian estimation is the determination of an effective informative prior. In hierarchical Bayes models, the uncertainty of hyperparameters in a prior can be further modeled via their own priors, namely, hyper priors. This study introduces a framework to construct hyper priors for both the mean and the variance…
Descriptors: Bayesian Statistics, Randomized Controlled Trials, Effect Size, Sampling
Hallberg, Kelly; Williams, Ryan; Swanlund, Andrew – Journal of Research on Educational Effectiveness, 2020
More aggregate data on school performance is available than ever before, opening up new possibilities for applied researchers interested in assessing the effectiveness of school-level interventions quickly and at a relatively low cost by implementing comparative interrupted times series (CITS) designs. We examine the extent to which effect…
Descriptors: Data Use, Research Methodology, Program Effectiveness, Design
Opper, Isaac M. – RAND Corporation, 2020
Researchers often include covariates when they analyze the results of randomized controlled trials (RCTs), valuing the increased precision of the estimates over the potential of inducing small-sample bias when doing so. In this paper, we develop a sufficient condition which ensures that the inclusion of covariates does not induce small-sample bias…
Descriptors: Artificial Intelligence, Man Machine Systems, Educational Technology, Technology Uses in Education
VanHoudnos, Nathan – Society for Research on Educational Effectiveness, 2016
Cluster randomized experiments are ubiquitous in modern education research. Although a variety of modeling approaches are used to analyze these data, perhaps the most common methodology is a normal mixed effects model where some effects, such as the treatment effect, are regarded as fixed, and others, such as the effect of group random assignment…
Descriptors: Effect Size, Randomized Controlled Trials, Educational Experiments, Educational Research
Joyce, Ted; Remler, Dahlia K.; Jaeger, David A.; Altindag, Onur; O'Connell, Stephen D.; Crockett, Sean – Journal of Policy Analysis and Management, 2017
Randomized experiments provide unbiased estimates of treatment effects, but are costly and time consuming. We demonstrate how a randomized experiment can be leveraged to measure selection bias by conducting a subsequent observational study that is identical in every way except that subjects choose their treatment--a quasi-doubly randomized…
Descriptors: Randomized Controlled Trials, Quasiexperimental Design, Selection Criteria, Selection Tools
Tipton, Elizabeth; Pustejovsky, James E. – Society for Research on Educational Effectiveness, 2015
Randomized experiments are commonly used to evaluate the effectiveness of educational interventions. The goal of the present investigation is to develop small-sample corrections for multiple contrast hypothesis tests (i.e., F-tests) such as the omnibus test of meta-regression fit or a test for equality of three or more levels of a categorical…
Descriptors: Randomized Controlled Trials, Sample Size, Effect Size, Hypothesis Testing