Computing Variances and Covariances, Visualization and Missing Data Solution for Multivariate Meta-Analysis
Computing Variance-Covariance Matrices for Log Odds Ratios
Computing Covariance between Log Odds Ratio and Log Risk Ratio
Computing Covariance between Log Odds Ratio and Risk Difference
Computing Variance-Covariance Matrices for Log Risk Ratios
Computing Covariance between Log Risk Ratio and Risk Difference
Computing Variance-Covariance Matrices for Mean Differences
Computing Covariance between Mean Difference and Log Odds Ratio
Computing Covariance between Mean Difference and Log Risk Ratio
Computing Covariance between Mean Difference and Risk Difference
Computing Covariance between Mean Difference and Standardized Mean Dif...
Fitting Fixed-Effect Meta-Analysis Models
Multiple Imputation for Missing Data in Meta-Analysis
Computing Variances and Covariances, Visualization and Missing Data So...
Computing Variance-Covariance Matrices for Effect Sizes of the Same or...
Plot Confidence Intervals for a Meta-Analysis
Computing Variance-Covariance Matrices for Correlation Coefficients
Computing Variance-Covariance Matrices for Risk Differences
Computing Variance-Covariance Matrices for Standardized Mean Differenc...
Computing Covariance between Standardized Mean Difference and Log Odds...
Computing Covariance between Standardized Mean Difference and Log Risk...
Computing Covariance between Standardized Mean Difference and Risk Dif...
Collection of functions to compute within-study covariances for different effect sizes, data visualization, and single and multiple imputations for missing data. Effect sizes include correlation (r), mean difference (MD), standardized mean difference (SMD), log odds ratio (logOR), log risk ratio (logRR), and risk difference (RD).