In this course, you will :
- Although most researchers are aware of what meta-analysis is, few are aware of how to calculate an effect size from popular metrics such as risk ratios, or how the distinction between fixed and random effects can lead the meta-analyst astray.
- This advanced-level course for practitioners and researchers in data science and statistics covers raw mean differences—specifically for experimental and comparison groups—as well as how to convert useful outcome measures such as relative risk and odds ratios to commensurate measures of effect size.
- Discover how confidence intervals for binary outcome measures are calculated.
1. Meta-Analysis: The Basic Idea
- Combine many empirical findings
- Closer look at effect sizes
- Need for a standard measure
2. Two Groups: Continuous Outcome Measure
- Raw mean difference
- Standardized mean difference: Independent groups
- Standardized mean difference: Dependent groups
3. Two Groups: Binary Outcome
- Risk and odds ratios
- Logarithms in risk and odds ratios
4. Confidence Intervals
- Odds ratios
- Single study