Meta Analysis Flashcards
What role does effect size play in meta-analysis?
Effect size serves as a measure of the magnitude of the intervention effect observed in each study and is used to quantify the overall effect in meta-analysis.
How does meta-analysis handle studies with different methodologies or outcome measures?
Meta-analysis employs statistical techniques such as subgroup analysis or meta-regression to account for methodological differences across studies.
What is the difference between a fixed-effects model and a random-effects model?
A fixed-effects model assumes that all studies estimate the same underlying effect size, while a random-effects model accounts for variability in effect sizes across studies.
What factors can contribute to heterogeneity in meta-analysis results?
Heterogeneity in meta-analysis results can arise from differences in study populations, interventions, or outcome measures, among other factors.
Why is it important to assess the quality of included studies in meta-analysis?
Assessing the quality of included studies helps evaluate the reliability and validity of the evidence synthesized in meta-analysis.
What is the purpose of sensitivity analysis in meta-analysis?
Sensitivity analysis explores the robustness of meta-analysis results by examining the impact of excluding certain studies or changing analysis methods.
How can meta-analysis account for publication bias?
Meta-analysis can address publication bias through techniques such as funnel plot asymmetry assessment, trim-and-fill analysis, or Egger’s regression test.
What are the steps involved in conducting a meta-analysis?
Conducting a meta-analysis involves defining research questions, literature search, study selection, data extraction, analysis, and interpretation of results.
What statistical methods are used to calculate the overall effect size in meta-analysis?
Overall effect size in meta-analysis is typically calculated as a weighted average of effect sizes from individual studies, with weights proportional to study precision.
When might subgroup analysis be warranted in a meta-analysis?
Subgroup analysis may be conducted to explore potential sources of heterogeneity by comparing effect sizes across predefined subgroups of studies.
What are the limitations of subgroup analysis in meta-analysis?
Limitations of subgroup analysis include reduced statistical power, increased risk of spurious findings, and potential for overinterpretation of subgroup differences.
What are the potential biases associated with selecting studies for meta-analysis?
Biases in meta-analysis can arise from selective publication, language bias, citation bias, or funding bias, among others.
How can researchers ensure transparency and reproducibility in meta-analysis?
Transparency and reproducibility in meta-analysis can be ensured through preregistration of analysis plans, open data sharing, and detailed reporting of methods and results.
What strategies can be employed to minimize the impact of outliers in meta-analysis?
Strategies to minimize the impact of outliers in meta-analysis include sensitivity analysis, robust statistical methods, and visual inspection of data.
What is the difference between a narrative review and a meta-analysis?
A narrative review summarizes evidence qualitatively, while a meta-analysis quantitatively synthesizes data from multiple studies to estimate an overall effect size.