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Vote Counting and combined p values

Vote Counting and combined p values. Precursors to Meta-analysis. People are not intuitive statisticians. Statistical decision making is difficult General problem of cumulating evidence Prior knowledge & Bayes theorem. ES and p value. Independent samples t-test.

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Vote Counting and combined p values

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  1. Vote Counting and combined p values Precursors to Meta-analysis

  2. People are not intuitive statisticians • Statistical decision making is difficult • General problem of cumulating evidence • Prior knowledge & Bayes theorem

  3. ES and p value Independent samples t-test What happpens to t as N increases? p = f(ES, N) Standardized mean difference What happens to d as N increases?

  4. ES & Sample Size

  5. Predecessors (1) • Vote Counting • Collect sig tests • Count proportion significant • Majority rules • Provides wrong results if power is poor

  6. Example 3 of 11 studies are significant. Overall ES: .33 SD favors meditation.

  7. Predecessors (2) • Combine p values • Collect sig tests and combine p values • Ok for overall p value • Can be done with only sig test result • Doesn’t result in ES, only p • If you need to do this, see Rosenthal • Rosenthal, R. (1991). Meta-analytic procedures for social research. Newbury Park: Sage. • Genesis of Filedrawer analyses • Less emphasis today on significance tests.

  8. Vote Counting Exercise Correlations larger than this are significant Sample size Take 1,000 samples of size (50, 100, 200) from populations with rho (.10, .20, .30, .40). What proportion of observed correlations are significant?

  9. Discussion of Vote Counting • Why is vote counting a bad idea for evaluating a literature to decide if there is an effect? • What is the typical effect size in your area of research • Given the typical effect size in your research area, what sort of sample size do you think you will need to get a significant result in your thesis/dissertation?

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