Experimental
& Quasi-Experimental Resources
CEEP/SEI
Resources Produced for TAH Grantees
U.S.
Department of Education (U.S. Ed) documents/Resources
Annotated Bibliography of Experimental and
Quasi-experimental design Evaluation Resources
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Schneider, Barbara, Martin Carnoy, Jeremy
Kilpatrick, William H. Schmidt, and Richard J. Shavelson. 2007.
Estimating causal effects. American Educational Research Association.
This book was the result of a think tank white paper prepared
under the auspices of the AERA Grants Program. Topics included in the
book include forming an evidential base for causality, the logic of
causal inference, the formal specification of the causal inference
model, criteria for making causal inferences, issues in the design and
fielding of randomized experiments, estimating causal effects using
observational data, methods for approximating randomized assignment, and
case studies of NSF-supported research using the analysis of large-scale
datasets.
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Bickman, Leonard, ed. Validity and social experimentation: Donald
Campbell’s legacy Thousand Oaks, CA: Sage Publications, 2000.
This book is sponsored by the American Evaluation Association and
focuses on responses to Donald Campbells contributions to the concept of
validity as it applies to meta-analysis, subject selection problems in
randomized experiments, time-series designs and quasi-experiments, and
the logic of ruling out rival hypotheses |
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Boruch, Robert F. 1996. Randomized experiments for
planning and evaluation: a practical guide. Thousand Oaks, CA: Sage
Publications. A easy to follow textbook focused on how to
randomize experiments and analyze the data. |
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Boulmetis, John and Phyllis Dutwin. The ABCs of evaluation: timeless
techniques for program and project managers.:Jossey-Bass, 1999: This is a comprehensive, straight-forward source for persons without formal training in evaluation. It explains each component of evaluation design and implementation, describing different evaluation models with examples of how each model can be used and offering tips on data collection. Written from an education perspective.
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Chelimsky, Eleanor and William R. Shadish, eds. 1997.
Evaluation for the 21st century: a handbook. Thousand Oaks,
CA: Sage Publications. This is a helpful reference textbook with
examples of evaluation theory and practice by experts in the field. |
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Cook, Thomas D. and Donald T. Campbell. 1979.
Quasi-experimentation: design and analysis issues. Houghton Mifflin
Company. This is a “must have” book for anyone attempting to conduct
field research. It details a range of quasi-experimental approaches to “real
world” research and includes a discussion of the pitfalls that new and
inexperienced researchers most often make. It is a follow-up to Campbell
and Stanley’s (1966) “Experimental alnd Quasi-Experimental Designs for
Research.” |
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Evaluation Toolkit: Quasi-Experimental Design. Government of Canada:
(pdf) A toolkit detailing the basics of quasi-experimental design and
the need for comparison groups. |
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Mark, Melvin M., Gary T. Henry, and George Julnes.
2000. Evauation: an integrated framework for understanding, guiding, and
improving policies and programs. (September): Jossey-Bass. This is an
easy-to-read, practical and comprehensive guide to program evaluation from
an education perspective. |
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Denise D. Quigley,Jorge Muñoz and Alison Jacknowitz: Using a matched
sampling methodology to evaluate program effects: An illustration from
the University of California Outreach:
(WEB) The purpose of this report was to establish the feasibility of using a matched sampling methodology to investigate program effects and the methodology’s ability to establish the matched samples of elementary, middle, and high schools whose progress on key indicators can be tracked over time. |
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Rossi, Peter H., Mark W. Lipsey, and Howard E.
Freeman. 2004. Evaluation: a systematic approach. Seventh edition.
Thousand Oaks, CA: Sage Publications. This is a “must have” textbook
for anyone wanting to learn about program evaluation. It is a how-to from
start to finish, detailing the range of approaches for program evaluation. |
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Shadish, William R., Thomas D. Cook and Donald T. Campbell.
Experimental and quasi-experimental designs for generalized causal
inference. This on-line knowledgebase by William Trochim of
Cornell University includes a section on research design that provides
details related to randomized controlled trials, non-equivalent groups
design, and regression discontinuity design. |
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Other Websites and Resources
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