Experimental and Quasi-Experimental Designs for Generalized Causal Inference

Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and Quasi-Experimental Designs for Generalized Causal Inference. Houghton Mifflin.

Type

Book chapter

Intellectual base

Review or monograph

Year

2002

ISBN

9780395615560

Link

https://openlibrary.org/works/OL16277901Wmatched

Cited from

philosophy, statistics_experimental_design

Cited by

10 citations across 10 artifacts.

Each citation links to the sentence it supports in the citing article.

Primes

• Evidence
  • In science, data are evidence for or against hypotheses, with strength depending on study design (the trace-producing mechanism), replication (independent corroboration), and freedom from confounders (defeaters).

    This sourceTreats the strength of causal evidence as governed by study design and the systematic ruling-out of threats to validity (confounders) — the trace-producing-mechanism and defeater roles in science.

• Experimental Design
  • A design may be internally valid but fail to answer the right question or generalize to the target population, as Shadish, Cook, and Campbell (2002) systematize across the four validity types.

    This sourcesystematizes the four validity types (internal, external, construct, statistical conclusion) and develops design principles for navigating their trade-offs in real-world research.

• Washout Failure
  • In education research, testing a curriculum immediately after a prior intervention conflates the new pedagogy with carryover learning.

    This sourceTreats carryover, testing/practice effects, and period effects as threats to validity in repeated-measures and quasi-experimental designs.

Domain-specific

• Dependent and independent variables
  • Dependent and independent variables is a paired modeling-role distinction between an outcome variable whose variation is explained and an input variable treated as controlled, assigned, or explanatory within a stated scope.
• Statistical Conclusion Validity
  • Shadish, Cook, and Campbell distinguish this from internal validity, which asks whether observed covariation reflects a causal relationship, and from construct and external validity.

Mechanisms

• Before/After Analysis
  • Its central failure is the post hoc trap: because the change and the outcome are separated only by time

    This sourceShows that a one-group pretest–posttest difference can arise from maturation or history rather than the intervention.

• Before/After Constraint Monitoring
  • Its central failure mode is misattribution — crediting the relief for an improvement that was really regression to the mean
• Controlled Overlap Pilot
  • Its central hazard is external validity — a pilot in a sheltered subzone can succeed for reasons that will not survive full deployment (a hand-picked cohort, extra attention, a scale at which harms stay dilute).

    This sourceExplains that effects can differ between small-scale experiments and full-scale implementation, and that selecting especially ready participants can inflate effects relative to the broader population.

• External Validity Check
  • The discipline it formalizes is the classical worry about external validity — whether a result generalizes beyond the exact conditions that produced it.

    This sourceDefines external validity as whether a causal relationship holds across variations in persons, settings, treatments, and outcomes.

• Transfer Prototype Experiment
  • Its central threat is weak external validity

    This sourceDefines external validity as whether a pilot result generalizes to other populations or settings.

Verification

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Links previously used in the corpus

Before the registry existed this work was also linked 6 other ways.

• https://books.google.com/books/about/Experimental_and_quasi_experimental_desi.html?id=o7jaAAAAMAAJ ×3
• https://books.google.com/books/about/Experimental_and_Quasi_experimental_Desi.html?id=bhLLmgEACAAJ ×1
• https://books.google.com/books/about/Experimental_and_Quasi_experimental_Desi.html?id=o7jaAAAAMAAJ ×1
• https://search.worldcat.org/es/title/experimental-and-quasi-experimental-designs-for-generalized-causal-inference/oclc/606894072 ×1
• https://search.worldcat.org/title/10006500 ×1
• https://www.worldcat.org/oclc/47702762 ×1

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