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Chapter 11 Meta-Analysis
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Meta-analysis Quantitative means of reanalyzing the results from a large number of research studies in an attempt to synthesize findings More than merely a review of related literature Relatively new approach in HHP research
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Effect Size Basic statistic used in meta-analysis Converts results from different studies to a common metric so that comparisons can be made Used to estimate meaningfulness of an outcome (i.e., practical significance) –Not influenced by sample size
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Example Size Formula ES = (M e – M c )/S c Formula for estimating ES for difference between experimental and control group. Where M e is the mean of the experimental group, M c is the mean of the control group, and S c is the standard deviation of the control group. Note: There are numerous formulas that can be used to calculate ES.
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Interpretation of ES <.20 small.50medium >.80large Source: Cohen (1988)
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Meta -Analysis In meta-analysis, each research study contributes a data point to the subsequent analysis, much like an individual participant in a descriptive or experimental research study
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Steps in Meta-Analysis 1. Compile references There must be a substantial number of research studies available on a topic Requires means, standard deviations, correlations, etc. be published 2. Determine inclusive criteria E.g., published in last 10 years or N > 30 3. Review each study Record information needed to calculate ES from each study Identify and code moderator variables, if any
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Steps in Meta-Analysis cont. 4. Decide which studies to use 5. Do the meta-analysis Calculate the effect size for each study Generate summary statistics for effect sizes Examine according to moderator variables Interpret results 6. Report the results
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Criticism of Meta-Analysis Not the ultimate answer Does not differentiate in quality of studies Combines unlike studies with too much variability (i.e., mixing apples and oranges) Inappropriate coding of variables
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