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Garret J. Hall; Sophia Putzeys; Thomas R. Kratochwill; Joel R. Levin – Educational Psychology Review, 2024
Single-case experimental designs (SCEDs) have a long history in clinical and educational disciplines. One underdeveloped area in advancing SCED design and analysis is understanding the process of how internal validity threats and operational concerns are avoided or mitigated. Two strategies to ameliorate such issues in SCED involve replication and…
Descriptors: Research Design, Graphs, Case Studies, Validity
Thomas Cook; Mansi Wadhwa; Jingwen Zheng – Society for Research on Educational Effectiveness, 2023
Context: A perennial problem in applied statistics is the inability to justify strong claims about cause-and-effect relationships without full knowledge of the mechanism determining selection into treatment. Few research designs other than the well-implemented random assignment study meet this requirement. Researchers have proposed partial…
Descriptors: Observation, Research Design, Causal Models, Computation

Kenneth A. Frank; Qinyun Lin; Spiro J. Maroulis – Grantee Submission, 2024
In the complex world of educational policy, causal inferences will be debated. As we review non-experimental designs in educational policy, we focus on how to clarify and focus the terms of debate. We begin by presenting the potential outcomes/counterfactual framework and then describe approximations to the counterfactual generated from the…
Descriptors: Causal Models, Statistical Inference, Observation, Educational Policy
Weidlich, Joshua; Gaševic, Dragan; Drachsler, Hendrik – Journal of Learning Analytics, 2022
As a research field geared toward understanding and improving learning, Learning Analytics (LA) must be able to provide empirical support for causal claims. However, as a highly applied field, tightly controlled randomized experiments are not always feasible nor desirable. Instead, researchers often rely on observational data, based on which they…
Descriptors: Causal Models, Inferences, Learning Analytics, Comparative Analysis
Stephanie Moore; George Veletsianos; Michael K. Barbour – OTESSA Journal, 2022
While there has been a lot of debate over the impact of online and remote learning on mental health and well-being, there has been no systematic syntheses or reviews of the research on this particular issue. In this paper, we review the research on the relationship between mental health/well-being and online or remote learning. Our review shows…
Descriptors: Distance Education, Electronic Learning, Mental Health, Research Methodology
Wing, Coady; Bello-Gomez, Ricardo A. – American Journal of Evaluation, 2018
Treatment effect estimates from a "regression discontinuity design" (RDD) have high internal validity. However, the arguments that support the design apply to a subpopulation that is narrower and usually different from the population of substantive interest in evaluation research. The disconnect between RDD population and the…
Descriptors: Regression (Statistics), Research Design, Validity, Evaluation Methods
Tang, Yang; Cook, Thomas D.; Kisbu-Sakarya, Yasemin – Society for Research on Educational Effectiveness, 2015
Regression discontinuity design (RD) has been widely used to produce reliable causal estimates. Researchers have validated the accuracy of RD design using within study comparisons (Cook, Shadish & Wong, 2008; Cook & Steiner, 2010; Shadish et al, 2011). Within study comparisons examines the validity of a quasi-experiment by comparing its…
Descriptors: Pretests Posttests, Statistical Bias, Accuracy, Regression (Statistics)
Gelman, Andrew; Imbens, Guido – National Bureau of Economic Research, 2014
It is common in regression discontinuity analysis to control for high order (third, fourth, or higher) polynomials of the forcing variable. We argue that estimators for causal effects based on such methods can be misleading, and we recommend researchers do not use them, and instead use estimators based on local linear or quadratic polynomials or…
Descriptors: Regression (Statistics), Mathematical Models, Causal Models, Research Methodology
Wing, Coady; Cook, Thomas D. – Journal of Policy Analysis and Management, 2013
The sharp regression discontinuity design (RDD) has three key weaknesses compared to the randomized clinical trial (RCT). It has lower statistical power, it is more dependent on statistical modeling assumptions, and its treatment effect estimates are limited to the narrow subpopulation of cases immediately around the cutoff, which is rarely of…
Descriptors: Regression (Statistics), Research Design, Statistical Analysis, Research Problems
Devroop, Karendra – 2000
The purpose of this paper is to articulate the common confusion of correlation for causation. Various articles that have addressed this issue are reviewed, and possible reasons for the misinterpretation of correlation as causation are presented. The differences between correlational and experimental research designs are reviewed, and the…
Descriptors: Causal Models, Correlation, Research Design, Research Problems
Helberg, Clay – 1996
Abuses and misuses of statistics are frequent. This digest attempts to warn against these in three broad classes of pitfalls: sources of bias, errors of methodology, and misinterpretation of results. Sources of bias are conditions or circumstances that affect the external validity of statistical results. In order for a researcher to make…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Error of Measurement
Juan Carlos Calcagno; Bridget Terry Long – National Center for Postsecondary Research, 2008
Remedial or developmental courses are the most common policy instruments used to assist underprepared postsecondary students who are not ready for college-level coursework. However, despite its important role in higher education and its substantial costs, there is little rigorous evidence on the effectiveness of college remediation on the outcomes…
Descriptors: Educational Objectives, Academic Persistence, Outcomes of Education, Academic Achievement

Johnson, David E. – Teaching of Psychology, 1996
Provides an exercise for introducing research methods to undergraduates. The students view a graph revealing that left-handed people are underrepresented in older age groups. Small group discussions attempt to explain this phenomenon. A follow-up class discussion focuses on the different approaches and methods available for interpreting the data.…
Descriptors: Causal Models, Critical Thinking, Data Interpretation, Factor Analysis