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Quasi-Experimental Designs

Quasi-Experimental Designs. Quasi-Experimental Design. You cannot randomly assign experimental participants to groups You DO manipulate an IV You DO measure a DV. When to use quasi-experimental design?. Study participants in certain groups

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Quasi-Experimental Designs

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  1. Quasi-Experimental Designs

  2. Quasi-Experimental Design • You cannot randomly assign experimental participants to groups • You DO manipulate an IV • You DO measure a DV

  3. When to use quasi-experimental design? • Study participants in certain groups • Evaluate an ongoing or completed program/intervention • Study social conditions (examples: poverty, race, unemployment) • Expense, time, or monitoring difficulties • Ethical considerations

  4. Nonequivalent Groups Design • Structured like a pretest-postest randomized experiment • Key is to create as equal a comparison group as possible through our selection criteria N O X O (treatment) N O O (comparison)

  5. Nonequivalent Groups Design • Example: Geronimous (1991) • Typical outcomes for teen mothers: • Poverty, high-school dropout rates increase, higher infant mortality • Geronimous believed that family factors, like SES, were better predictors of outcomes than teen pregnancy • How to find a comparison group as similar as possible?

  6. Nonequivalent Groups Design: Analysis • Your groups began the experiment as not equivalent • So, the important question is not whether there was a difference • Is the difference the same as before the experiment?

  7. Nonequivalent Groups Design • Threats to Internal Validity • Maturation • Instrumentation • Statistical regression • Interaction between selection and history • Interpretation of findings must be more cautious, but a strong research design

  8. Interrupted Time-Series Design • Measure a group of participants repeatedly over time • Interrupt with a treatment • Measure participants repeatedly again O1 O2 O3 O4 X O5 O6 O7 O8

  9. Interrupted Time-Series Design • Threats to Internal Validity • History • Maturation • Instrumentation

  10. O1 O2 O3 O4 X O5 O6 O7 O8 O1 O2 O3 O4 O5 O6 O7 O8 Interrupted Time-Series Design • How to control for history threats? • Frequent measurement intervals • Comparison group

  11. Interrupted Time-Series Design • How to control for history threats? • Frequent measurement intervals • Comparison group • Measure, treatment, measure, then “undo” the treatment, measure again • Not always feasible

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