Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 0 |
Since 2006 (last 20 years) | 10 |
Descriptor
Research Design | 10 |
Computation | 5 |
Effect Size | 4 |
Causal Models | 3 |
Comparative Analysis | 3 |
Correlation | 3 |
Intervention | 3 |
Meta Analysis | 3 |
Statistical Analysis | 3 |
Validity | 3 |
Behavioral Science Research | 2 |
More ▼ |
Source
Online Submission | 3 |
Psychological Methods | 2 |
Journal of Educational and… | 1 |
Journal of Policy Analysis… | 1 |
Remedial and Special Education | 1 |
Research Synthesis Methods | 1 |
Research on Social Work… | 1 |
Author
Publication Type
Journal Articles | 10 |
Reports - Research | 6 |
Reports - Evaluative | 3 |
Information Analyses | 1 |
Reports - Descriptive | 1 |
Education Level
Higher Education | 1 |
Kindergarten | 1 |
Audience
Location
Germany | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
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
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
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
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
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
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
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
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