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Shadish, William R.; Hedges, Larry V.; Horner, Robert H.; Odom, Samuel L. – National Center for Education Research, 2015
The field of education is increasingly committed to adopting evidence-based practices. Although randomized experimental designs provide strong evidence of the causal effects of interventions, they are not always feasible. For example, depending upon the research question, it may be difficult for researchers to find the number of children necessary…
Descriptors: Effect Size, Case Studies, Research Design, Observation
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Hitchcock, John H.; Horner, Robert H.; Kratochwill, Thomas R.; Levin, Joel R.; Odom, Samuel L.; Rindskopf, David M.; Shadish, William R. – Remedial and Special Education, 2014
In this article, we respond to Wolery's critique of the What Works Clearinghouse (WWC) pilot "Standards," which were developed by the current authors. We do so to provide additional information and clarify some points previously summarized in this journal. We also respond to several concerns raised by Maggin, Briesch, and Chafouleas…
Descriptors: Research Design, Standards, Evidence, Clearinghouses
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Sullivan, Kristynn J.; Shadish, William R. – Society for Research on Educational Effectiveness, 2013
Single case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time both in the presence and absence of treatment. For a variety of reasons, interest in the statistical analysis and meta-analysis of these designs has been growing in recent years. This paper proposes modeling SCD data with…
Descriptors: Models, Longitudinal Studies, Data, Research Design
Shadish, William R.; Rindskopf, David M.; Hedges, Larry V.; Sullivan, Kristynn J. – Online Submission, 2012
Researchers in the single-case design tradition have debated the size and importance of the observed autocorrelations in those designs. All of the past estimates of the autocorrelation in that literature have taken the observed autocorrelation estimates as the data to be used in the debate. However, estimates of the autocorrelation are subject to…
Descriptors: Bayesian Statistics, Research Design, Correlation, Computation
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Pustejovsky, James E.; Hedges, Larry V.; Shadish, William R. – Journal of Educational and Behavioral Statistics, 2014
In single-case research, the multiple baseline design is a widely used approach for evaluating the effects of interventions on individuals. Multiple baseline designs involve repeated measurement of outcomes over time and the controlled introduction of a treatment at different times for different individuals. This article outlines a general…
Descriptors: Hierarchical Linear Modeling, Effect Size, Maximum Likelihood Statistics, Computation
Hedges, Larry V.; Pustejovsky, James E.; Shadish, William R. – Online Submission, 2012
Single case designs are a set of research methods for evaluating treatment effects by assigning different treatments to the same individual and measuring outcomes over time and are used across fields such as behavior analysis, clinical psychology, special education, and medicine. Emerging standards for single case designs have focused attention on…
Descriptors: Research Design, Effect Size, Meta Analysis, Computation
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Hedges, Larry V.; Pustejovsky, James E.; Shadish, William R. – Research Synthesis Methods, 2013
Single-case designs are a class of research methods for evaluating treatment effects by measuring outcomes repeatedly over time while systematically introducing different condition (e.g., treatment and control) to the same individual. The designs are used across fields such as behavior analysis, clinical psychology, special education, and…
Descriptors: Effect Size, Research Design, Research Methodology, Behavioral Science Research
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Marcus, Sue M.; Stuart, Elizabeth A.; Wang, Pei; Shadish, William R.; Steiner, Peter M. – Psychological Methods, 2012
Although randomized studies have high internal validity, generalizability of the estimated causal effect from randomized clinical trials to real-world clinical or educational practice may be limited. We consider the implication of randomized assignment to treatment, as compared with choice of preferred treatment as it occurs in real-world…
Descriptors: Educational Practices, Program Effectiveness, Validity, Causal Models
Shadish, William R.; Sullivan, Kristynn J. – Online Submission, 2011
The purpose of this study was to identify the characteristics of a representative sample of single-case designs that appear in the published literature. The study located, digitized, and coded all 809 single-case designs appearing in 113 studies in the year 2008 in 21 journals in a variety of fields in psychology and education. Coded variables…
Descriptors: Research Design, Intervention, Periodicals, Educational Research
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Shadish, William R. – Research on Social Work Practice, 2011
This article reviews several decades of the author's meta-analytic and experimental research on the conditions under which nonrandomized experiments can approximate the results from randomized experiments (REs). Several studies make clear that we can expect accurate effect estimates from the regression discontinuity design, though its statistical…
Descriptors: Control Groups, Comparative Analysis, Outcomes of Treatment, Meta Analysis
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Shadish, William R. – Psychological Methods, 2010
This article compares Donald Campbell's and Donald Rubin's work on causal inference in field settings on issues of epistemology, theories of cause and effect, methodology, statistics, generalization, and terminology. The two approaches are quite different but compatible, differing mostly in matters of bandwidth versus fidelity. Campbell's work…
Descriptors: Inferences, Generalization, Epistemology, Causal Models
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Cook, Thomas D.; Shadish, William R.; Wong, Vivian C. – Journal of Policy Analysis and Management, 2008
This paper analyzes 12 recent within-study comparisons contrasting causal estimates from a randomized experiment with those from an observational study sharing the same treatment group. The aim is to test whether different causal estimates result when a counterfactual group is formed, either with or without random assignment, and when statistical…
Descriptors: Causal Models, Experiments, Pretests Posttests, Job Training