Reference

Meta-analysis Overall effect sizes and CIs across groups of studies
meta.ave.agree()	Confidence interval for an average G-index agreement coefficient
meta.ave.cor.gen()	Confidence interval for an average correlation of any type
meta.ave.cor()	Confidence interval for an average Pearson or partial correlation
meta.ave.cronbach()	Confidence interval for an average Cronbach alpha reliability
meta.ave.fisher()	Fisher confidence interval for an average correlation.
meta.ave.gen.cc()	Confidence interval for an average effect size using a constant coefficient model
meta.ave.gen.rc()	Confidence interval for an average effect size using a random coefficient model
meta.ave.gen()	Confidence interval for an average of any parameter
meta.ave.mean.ps()	Confidence interval for an average mean difference from paired-samples studies
meta.ave.mean2()	Confidence interval for an average mean difference from 2-group studies
meta.ave.meanratio.ps()	Confidence interval for an average mean ratio from paired-samples studies
meta.ave.meanratio2()	Confidence interval for an average mean ratio from 2-group studies
meta.ave.odds()	Confidence interval for average odds ratio from 2-group studies
meta.ave.path()	Confidence interval for an average slope coefficient in a general linear model or a path model.
meta.ave.pbcor()	Confidence interval for an average point-biserial correlation
meta.ave.plot()	Forest plot for average effect sizes
meta.ave.prop.ps()	Confidence interval for an average proportion difference in paired-samples studies
meta.ave.prop2()	Confidence interval for an average proportion difference in 2-group studies
meta.ave.propratio2()	Confidence interval for an average proportion ratio from 2-group studies
meta.ave.semipart()	Confidence interval for an average semipartial correlation
meta.ave.slope()	Confidence interval for an average slope coefficient
meta.ave.spear()	Confidence interval for an average Spearman correlation
meta.ave.stdmean.ps()	Confidence interval for an average standardized mean difference from paired-samples studies
meta.ave.stdmean2()	Confidence interval for an average standardized mean difference from 2-group studies
meta.ave.var()	Confidence interval for an average variance
Meta-analysis of categorical moderators Estimate differences between linear contrasts of groups of studies
meta.lc.agree()	Confidence interval for a linear contrast of G-index coefficients
meta.lc.gen()	Confidence interval for a linear contrast of effect sizes
meta.lc.mean.ps()	Confidence interval for a linear contrast of mean differences from paired-samples studies
meta.lc.mean1()	Confidence interval for a linear contrast of means
meta.lc.mean2()	Confidence interval for a linear contrast of mean differences from 2-group studies
meta.lc.meanratio.ps()	Confidence interval for a log-linear contrast of mean ratios from paired-samples studies
meta.lc.meanratio2()	Confidence interval for a log-linear contrast of mean ratios from 2-group studies
meta.lc.odds()	Confidence interval for a log-linear contrast of odds ratios
meta.lc.prop.ps()	Confidence interval for a linear contrast of proportion differences in paired-samples studies
meta.lc.prop1()	Confidence interval for a linear contrast of proportions
meta.lc.prop2()	Confidence interval for a linear contrast of proportion differences in 2-group studies
meta.lc.propratio2()	Confidence interval for a log-linear contrast of proportion ratios from 2-group studies
meta.lc.stdmean.ps()	Confidence interval for a linear contrast of standardized mean differences from paired-samples studies
meta.lc.stdmean2()	Confidence interval for a linear contrast of standardized mean differences from 2-group studies
Meta-regression Estimate relationships between quantitative predictors and effect sizes in groups of studies
meta.lm.agree()	Meta-regression analysis for G agreement indices
meta.lm.cor.gen()	Meta-regression analysis for correlations
meta.lm.cor()	Meta-regression analysis for Pearson or partial correlations
meta.lm.cronbach()	Meta-regression analysis for Cronbach reliabilities
meta.lm.gen()	Meta-regression analysis for any type of effect size
meta.lm.mean.ps()	Meta-regression analysis for paired-samples mean differences
meta.lm.mean1()	Meta-regression analysis for 1-group means
meta.lm.mean2()	Meta-regression analysis for 2-group mean differences
meta.lm.meanratio.ps()	Meta-regression analysis for paired-samples log mean ratios
meta.lm.meanratio2()	Meta-regression analysis for 2-group log mean ratios
meta.lm.odds()	Meta-regression analysis for odds ratios
meta.lm.prop.ps()	Meta-regression analysis for paired-samples proportion differences
meta.lm.prop1()	Meta-regression analysis for 1-group proportions
meta.lm.prop2()	Meta-regression analysis for 2-group proportion differences
meta.lm.propratio2()	Meta-regression analysis for proportion ratios
meta.lm.semipart()	Meta-regression analysis for semipartial correlations
meta.lm.spear()	Meta-regression analysis for Spearman correlations
meta.lm.stdmean.ps()	Meta-regression analysis for paired-samples standardized mean differences
meta.lm.stdmean2()	Meta-regression analysis for 2-group standardized mean differences
Meta-sub Estimate differences in relationships found in groups of studies
meta.sub.cor()	Confidence interval for a subgroup difference in average Pearson or partial correlations
meta.sub.cronbach()	Confidence interval for a subgroup difference in average Cronbach reliabilities
meta.sub.gen()	Confidence interval for a subgroup difference in average effect size
meta.sub.pbcor()	Confidence interval for a subgroup difference in average point-biserial correlations
meta.sub.semipart()	Confidence interval for a subgroup difference in average semipartial correlations
meta.sub.spear()	Confidence interval for a subgroup difference in average Spearman correlations
Replication Compare original and replication results
replicate.cor.gen()	Compares and combines any type of correlation in original and follow-up studies
replicate.cor()	Compares and combines Pearson or partial correlations in original and follow-up studies
replicate.gen()	Compares and combines effect sizes in original and follow-up studies
replicate.mean.ps()	Compares and combines paired-samples mean differences in original and follow-up studies
replicate.mean1()	Compares and combines single mean in original and follow-up studies
replicate.mean2()	Compares and combines 2-group mean differences in original and follow-up studies
replicate.oddsratio()	Compares and combines odds ratios in original and follow-up studies
replicate.plot()	Plot to compare estimates from original and follow-up studies
replicate.prop.ps()	Compares and combines paired-samples proportion differences in original and follow-up studies
replicate.prop1()	Compares and combines single proportion in original and follow-up studies
replicate.prop2()	Compares and combines 2-group proportion differences in original and follow-up studies
replicate.ratio.prop2()	Compares and combines 2-group proportion ratios in original and follow-up studies
replicate.slope()	Compares and combines slope coefficients in original and follow-up studies
replicate.spear()	Compares and combines Spearman correlations in original and follow-up studies
replicate.stdmean.ps()	Compares and combines paired-samples standardized mean differences in original and follow-up studies
replicate.stdmean2()	Compares and combines 2-group standardized mean differences in original and follow-up studies
Standard errors Standard errors for various effects
se.ave.cor.nonover()	Computes the standard error for the average of two Pearson correlations with no variables in common that have been estimated from the same sample
se.ave.cor.over()	Computes the standard error for the average of two Pearson correlations with one variable in common that have been estimated from the same sample
se.ave.mean2.dep()	Computes the standard error for the average of 2-group mean differences from two parallel measurement response variables in the same sample
se.biphi()	Computes the standard error for a biserial-phi correlation
se.bscor()	Computes the standard error for a biserial correlation
se.cohen()	Computes the standard error for Cohen's d
se.cor()	Computes the standard error for a Pearson or partial correlation
se.mean.ps()	Computes the standard error for a paired-samples mean difference
se.mean2()	Computes the standard error for a 2-group mean difference
se.meanratio.ps()	Computes the standard error for a paired-samples log mean ratio
se.meanratio2()	Computes the standard error for a 2-group log mean ratio
se.odds()	Computes the standard error for a log odds ratio
se.pbcor()	Computes the standard error for a point-biserial correlation
se.prop.ps()	Computes the estimate and standard error for a paired-samples proportion difference
se.prop2()	Computes the estimate and standard error for a 2-group proportion difference
se.semipartial()	Computes the standard error for a semipartial correlation
se.slope()	Computes a slope and standard error
se.spear()	Computes the standard error for a Spearman correlation
se.stdmean.ps()	Computes the standard error for a paired-samples standardized mean difference
se.stdmean2()	Computes the standard error for a 2-group standardized mean difference
se.tetra()	Computes the standard error for a tetrachoric correlation approximation
Miscellaneous Additional functions
meta.ave.fisher()	Fisher confidence interval for an average correlation.
cor.from.t()	Computes Pearson correlation between paired measurements from t statistic
meta.chitest()	Computes a chi-square test of effect-size homogeneity
stdmean2.from.t()	Computes Cohen's d from pooled-variance t statistic
table.from.odds()	Computes the cell frequencies in a 2x2 table using the marginal proportions and odds ratio
table.from.phi()	Computes the cell frequencies in a 2x2 table using the marginal proportions and phi correlation