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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)
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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
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Cook, Thomas D.; Scriven, Michael; Coryn, Chris L. S.; Evergreen, Stephanie D. H. – American Journal of Evaluation, 2010
Legitimate knowledge claims about causation have been a central concern among evaluators and applied researchers for several decades and often have been the subject of heated debates. In recent years these debates have resurfaced with a renewed intensity, due in part to the priority currently being given to randomized experiments by many funders…
Descriptors: Evaluators, Research Design, Causal Models, Inferences
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Wong, Manyee; Cook, Thomas D.; Steiner, Peter M. – Journal of Research on Educational Effectiveness, 2015
Some form of a short interrupted time series (ITS) is often used to evaluate state and national programs. An ITS design with a single treatment group assumes that the pretest functional form can be validly estimated and extrapolated into the postintervention period where it provides a valid counterfactual. This assumption is problematic. Ambiguous…
Descriptors: Evaluation Methods, Time, Federal Legislation, Educational Legislation
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Cook, Thomas D.; Steiner, Peter M. – Psychological Methods, 2010
In this article, we note the many ontological, epistemological, and methodological similarities between how Campbell and Rubin conceptualize causation. We then explore 3 differences in their written emphases about individual case matching in observational studies. We contend that (a) Campbell places greater emphasis than Rubin on the special role…
Descriptors: Research Methodology, Pretests Posttests, Data Analysis, Evaluation Methods
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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
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Cook, Thomas D. – New Directions for Evaluation, 2000
Offers a critical commentary on theory-based evaluation, stressing its utility as a method of program planning and as an adjunct to experiments but rejecting it as an alternative to experiments. Cites seven reasons for doubting that theory-based evaluations can provide the valid conclusions about a program's causal effects that proponents have…
Descriptors: Causal Models, Evaluation Methods, Experiments, Planning
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Cook, Thomas D. – New Directions for Program Evaluation, 1993
A practical theory is offered for probing external validity, the generalization of causal relationships. This alternative theory is built around five principles abstracted from research on construct validation. It emphasizes purposive sampling for theoretical ends rather than random sampling to represent a population. (SLD)
Descriptors: Causal Models, Construct Validity, Generalization, Research Methodology