Chapter 11 Meta-Analysis

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

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

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.

Interpretation of ES <.20 small.50medium >.80large Source: Cohen (1988)

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

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 > Review each study Record information needed to calculate ES from each study Identify and code moderator variables, if any

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

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