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Shao, Lucy; Levine, Richard A.; Guarcello, Maureen A.; Wilke, Morten C.; Stronach, Jeanne; Frazee, James P.; Fan, Juanjuan – International Journal of Artificial Intelligence in Education, 2023
Propensity score matching and weighting methods are applied to balance covariates and reduce selection bias in the analysis of observational study data, and ultimately estimate a treatment effect. We wish to evaluate the impact of a Supplemental Instruction (SI) program on student success in an Introductory Statistics course. In such student…
Descriptors: Statistical Bias, Probability, Scores, Weighted Scores
Hong, Guanglei; Qin, Xu; Yang, Fan – Journal of Educational and Behavioral Statistics, 2018
Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…
Descriptors: Statistical Inference, Probability, Statistical Bias, Statistical Analysis
Finucane, Mariel McKenzie; Martinez, Ignacio; Cody, Scott – American Journal of Evaluation, 2018
In the coming years, public programs will capture even more and richer data than they do now, including data from web-based tools used by participants in employment services, from tablet-based educational curricula, and from electronic health records for Medicaid beneficiaries. Program evaluators seeking to take full advantage of these data…
Descriptors: Bayesian Statistics, Data Analysis, Program Evaluation, Randomized Controlled Trials
Feller, Avi; Mealli, Fabrizia; Miratrix, Luke – Journal of Educational and Behavioral Statistics, 2017
Researchers addressing posttreatment complications in randomized trials often turn to principal stratification to define relevant assumptions and quantities of interest. One approach for the subsequent estimation of causal effects in this framework is to use methods based on the "principal score," the conditional probability of belonging…
Descriptors: Scores, Probability, Computation, Program Evaluation
Sude, Yujie; DeAngelis, Corey A.; Wolf, Patrick J. – Journal of School Choice, 2018
Since school voucher funds are public, policymakers fiercely debate how those funds should be spent. A goal of many decision-makers is to ensure that every private school option is "high-quality" through program accountability regulations. Private schools, however, decide whether to participate in a private school choice program and…
Descriptors: School Involvement, Educational Vouchers, Decision Making, Public Schools
White, Mark C.; Rowan, Brian; Hansen, Ben; Lycurgus, Timothy – Journal of Research on Educational Effectiveness, 2019
There is growing pressure to make efficacy experiments more useful. This requires attending to the twin goals of generalizing experimental results to those schools that will use the results and testing the intervention's theory of action. We show how electronic records, created naturally during the daily operation of technology-based…
Descriptors: Program Evaluation, Generalization, Experiments, Records (Forms)
Rein, Benjamin A.; McNeil, Daniel W.; Hayes, Allison R.; Hawkins, T. Anne; Ng, H. Mei; Yura, Catherine A. – Journal of American College Health, 2018
Objective: Training programs exist that prepare college students, faculty, and staff to identify and support students potentially at risk for suicide. Kognito is an online program that trains users through simulated interactions with virtual humans. This study evaluated Kognito's effectiveness in preparing users to intervene with at-risk students.…
Descriptors: College Students, Program Evaluation, Suicide, Prevention
Guarcello, Maureen A.; Levine, Richard A.; Beemer, Joshua; Frazee, James P.; Laumakis, Mark A.; Schellenberg, Stephen A. – Technology, Knowledge and Learning, 2017
Supplemental Instruction (SI) is a voluntary, non-remedial, peer-facilitated, course-specific intervention that has been widely demonstrated to increase student success, yet concerns persist regarding the biasing effects of disproportionate participation by already higher-performing students. With a focus on maintaining access for all students, a…
Descriptors: Peer Teaching, Supplementary Education, College Students, Student Participation
Nilsson, Andreas; Bergquist, Magnus; Schultz, Wesley P. – Environmental Education Research, 2017
When implementing environmental education and interventions to promote one pro-environmental behavior, it is seldom asked if and how non-target pro-environmental behaviors are affected. The spillover effect proposes that engaging in one behavior affects the probability of engagement or disengaging in a second behavior. Therefore, the positive…
Descriptors: Environmental Education, Intervention, Probability, Positive Behavior Supports
Piccone, Jason E. – Journal of Correctional Education, 2015
The effective evaluation of correctional programs is critically important. However, research in corrections rarely allows for the randomization of offenders to conditions of the study. This limitation compromises internal validity, and thus, causal conclusions can rarely be drawn. Increasingly, researchers are employing propensity score matching…
Descriptors: Correctional Education, Program Evaluation, Probability, Scores
Newton, Nicola C.; Conrod, Patricia J.; Slade, Tim; Carragher, Natacha; Champion, Katrina E.; Barrett, Emma L.; Kelly, Erin V.; Nair, Natasha K.; Stapinski, Lexine; Teesson, Maree – Journal of Child Psychology and Psychiatry, 2016
Background: This study investigated the long-term effectiveness of Preventure, a selective personality-targeted prevention program, in reducing the uptake of alcohol, harmful use of alcohol, and alcohol-related harms over a 3-year period. Methods: A cluster randomized controlled trial was conducted to assess the effectiveness of Preventure.…
Descriptors: Program Effectiveness, Prevention, Alcohol Abuse, Randomized Controlled Trials
Stanford, Courtney; Cole, Renee; Froyd, Jeff; Henderson, Charles; Friedrichsen, Debra; Khatri, Raina – Journal of Science Education and Technology, 2017
Increasing adoption and adaptation of promising instructional strategies and materials has been identified as a critical component needed to improve science, technology, engineering, and mathematics (STEM) education. This paper examines typical propagation practices and resulting outcomes of proposals written by developers of educational…
Descriptors: STEM Education, Educational Development, Educational Strategies, Program Proposals
Klerman, Jacob Alex; Olsho, Lauren E. W.; Bartlett, Susan – American Journal of Evaluation, 2015
While regression discontinuity has usually been applied retrospectively to secondary data, it is even more attractive when applied prospectively. In a prospective design, data collection can be focused on cases near the discontinuity, thereby improving internal validity and substantially increasing precision. Furthermore, such prospective…
Descriptors: Regression (Statistics), Evaluation Methods, Evaluation Problems, Probability
Tipton, Elizabeth; Hedges, Larry; Vaden-Kiernan, Michael; Borman, Geoffrey; Sullivan, Kate; Caverly, Sarah – Journal of Research on Educational Effectiveness, 2014
Randomized experiments are often seen as the "gold standard" for causal research. Despite the fact that experiments use random assignment to treatment conditions, units are seldom selected into the experiment using probability sampling. Very little research on experimental design has focused on how to make generalizations to well-defined…
Descriptors: Probability, Inferences, Eligibility, Recruitment
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