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Collier, Zachary K.; Zhang, Haobai; Liu, Liu – Practical Assessment, Research & Evaluation, 2022
Although educational research and evaluation generally occur in multilevel settings, many analyses ignore cluster effects. Neglecting the nature of data from educational settings, especially in non-randomized experiments, can result in biased estimates with long-term consequences. Our manuscript improves the availability and understanding of…
Descriptors: Artificial Intelligence, Probability, Scores, Educational Research
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Powell, Marvin G.; Hull, Darrell M.; Beaujean, A. Alexander – Journal of Experimental Education, 2020
Randomized controlled trials are not always feasible in educational research, so researchers must use alternative methods to study treatment effects. Propensity score matching is one such method for observational studies that has shown considerable growth in popularity since it was first introduced in the early 1980s. This paper outlines the…
Descriptors: Probability, Scores, Observation, Educational Research
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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
Cecile C. Dietrich; Eric J. Lichtenberger – Sage Research Methods Cases, 2016
We present a case study of the process through which a methodology was developed and applied to a quasi-experimental research study that employed propensity score matching. Methodological decisions are discussed and summarized, including an explanation of the approaches selected for each step in the study as well as rationales for these…
Descriptors: Test Construction, Quasiexperimental Design, Community Colleges, Fees
Imbens, Guido W.; Rubin, Donald B. – Cambridge University Press, 2015
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding…
Descriptors: Causal Models, Statistical Inference, Statistics, Social Sciences
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Liu, Leping; Ripley, Darren – International Journal of Technology in Teaching and Learning, 2014
Propensity score matching (PSM) has been used to estimate causal effects of treatment, especially in studies where random assignment to treatment is difficult to obtain. The main purpose of this article is to provide some practical guidance for propensity score sample matching, including definitions, procedures, decisions on each step, and methods…
Descriptors: Probability, Scores, Technology Integration, Science Education
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Tanner-Smith, Emily E.; Lipsey, Mark W. – Peabody Journal of Education, 2014
There are many situations where random assignment of participants to treatment and comparison conditions may be unethical or impractical. This article provides an overview of propensity score techniques that can be used for estimating treatment effects in nonrandomized quasi-experimental studies. After reviewing the logic of propensity score…
Descriptors: Probability, Scores, Quasiexperimental Design, High Schools
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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
Rothstein, Jesse; Mathis, William J. – National Education Policy Center, 2013
The Gates Foundation's Measures of Effective Teaching (MET) project was a multi-year study of thousands of teachers in six school districts that concluded in January 2013. This review addresses two of the final MET research papers. One paper uses random assignment to test for bias in teachers' value-added scores. The experimental protocol was…
Descriptors: Teacher Effectiveness, Teacher Evaluation, Longitudinal Studies, Student Placement
Dong, Nianbo – Society for Research on Educational Effectiveness, 2011
The purpose of this study is through Monte Carlo simulation to compare several propensity score methods in approximating factorial experimental design and identify best approaches in reducing bias and mean square error of parameter estimates of the main and interaction effects of two factors. Previous studies focused more on unbiased estimates of…
Descriptors: Research Design, Probability, Monte Carlo Methods, Simulation
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Bai, Haiyan – International Journal of Research & Method in Education, 2011
Propensity score matching (PSM) has become a popular approach for research studies when randomization is infeasible. However, there are significant differences in the effectiveness of selection bias reduction among the existing PSM methods and, therefore, it is challenging for researchers to select an appropriate matching method. This current…
Descriptors: Research Methodology, Researchers, Comparative Analysis, Scores
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Austin, Peter C. – Multivariate Behavioral Research, 2011
Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data. In this article we provide a practical illustration of the appropriate steps in conducting propensity score analyses. For illustrative purposes, we use a sample of current smokers who were discharged alive after being…
Descriptors: Smoking, Hospitals, Program Effectiveness, Probability
Zimmer, Ron; Gill, Brian; Booker, Kevin; Lavertu, Stephane; Sass, Tim R.; Witte, John – RAND Corporation, 2009
The first U.S. charter school opened in 1992, and the scale of the charter movement has since grown to 4,000 schools and more than a million students in 40 states plus the District of Columbia. With this growth has also come a contentious debate about the effects of the schools on their own students and on students in nearby traditional public…
Descriptors: Charter Schools, Research Methodology, Probability, Student Characteristics
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers