publication-bias-detection
Detect and assess publication bias in meta-analysis using funnel plots, Egger's test, trim-and-fill, and selection models. Use when users need to evaluate whether missing studies might affect their conclusions.
trial-sequential-analysis
Teach Trial Sequential Analysis (TSA) for controlling type I and II errors in cumulative meta-analyses. Use when users need to assess if meta-analysis has sufficient information, want to avoid premature conclusions, or need to plan future trials.
heterogeneity-analysis
Assess and interpret between-study heterogeneity in meta-analysis using I², Q statistic, tau², and prediction intervals. Use when users need to evaluate consistency across studies, understand sources of variation, or decide if pooling is appropriate.
ipd-meta-analysis
Teach Individual Patient Data (IPD) meta-analysis methods for analyzing raw participant-level data from multiple studies. Use when users have access to original datasets, need to explore treatment-effect modifiers, or want to conduct time-to-event analyses.
bayesian-meta-analysis
Teach Bayesian approaches to meta-analysis including prior specification, MCMC methods, and interpretation of posterior distributions. Use when users want to incorporate prior knowledge, need probabilistic interpretations, or are working with sparse data.
network-meta-analysis
Teach network meta-analysis (NMA) for comparing multiple treatments simultaneously. Use when users need to compare more than two interventions, understand indirect comparisons, or create network plots and league tables.
meta-analysis-fundamentals
Teach the foundational concepts of meta-analysis including effect sizes, statistical models, and evidence synthesis. Use when users ask about meta-analysis basics, want to understand pooled effects, or need guidance on fixed vs random effects models.
diagnostic-meta-analysis
Teach meta-analysis of diagnostic test accuracy studies including sensitivity, specificity, SROC curves, and bivariate models. Use when users need to synthesize diagnostic accuracy data, understand SROC curves, or assess quality with QUADAS-2.