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1. Sampling & External Validity. 2. Chapter 2. External Validity: Critiquing. 1. External Validity: Critiquing. The sampling model… Goal (claim) is representative sampling Often not attainable - Who to generalize to? Availability of the true “representative” sample?

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Presentation Transcript
external validity critiquing1
External Validity: Critiquing
  • The sampling model…
    • Goal (claim) is representative sampling
      • Often not attainable -
        • Who to generalize to?
        • Availability of the true “representative” sample?
        • Will the sample be representative of other times?
  • An alternative is to model (or critique) the differences in a systematic way…

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external validity critiquing2
External Validity: Critiquing
  • Proximal similarity model (Campbell, 1963)

this is the crux of it

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external validity critiquing3
External Validity: Critiquing
  • Proximal similarity model (Campbell, 1963)
    • The idea here is to quantify the difference between the various properties of the study you are considering, and that to which you want to generalize, and then consider the likelihood that this difference would alter the research’s findings

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external validity critiquing4
External Validity: Critiquing
  • Critiquing and responding to (improving) external validity
    • Sampling model (depends upon…)
      • Random sample (impossible)
      • Minimal drop out
    • Proximal similarity
      • Evaluate, critique, consider…

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sampling terminology
Sampling Terminology

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  • Population — the group to whom you wish to generalize
    • Theoretical
    • Accessible
  • Sampling frame — the listing of the accessible population from which you’ll draw your sample (or the procedure by which you’ll draw them)
  • Sample — the group of people you select to be in your study

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the sampling distribution
The Sampling Distribution

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  • How do you get from a sample statistic to an estimate of the population parameter?
  • The distribution of an infinite number of samples of the same size as the sample in your study
  • “Average of the averages” is close to the population parameter
  • Sampling distribution is theoretical
  • Standard error and the 65, 95, 99 percent rule

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