R: Visualization and Estimation of Effect Sizes

# Visualization and Estimation of Effect Sizes

## Documentation for package ‘esvis’ version 0.3.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

auc | Compute the Area Under the pp_plot Curve Calculates the area under the 'pp' curve. The area under the curve is also a useful effect-size like statistic, representing the probability that a randomly selected individual from the 'x' distribution will have a higher value than a randomly selected individual from the 'y' distribution.
benchmarks | Synthetic benchmark screening data
binned_es | Calculate binned effect sizes
binned_plot | Quantile-binned effect size plot
coh_d | Compute Cohen's _d_
ecdf_plot | Empirical Cumulative Distribution Plot
hedg_g | Compute Hedges' _g_ This function calculates effect sizes in terms of Hedges' _g_, also called the corrected (for sample size) effect size. See 'coh_d' for the uncorrected version. Also see Lakens (2013) for a discussion on different types of effect sizes and their interpretation. Note that missing data are removed from the calculations of the means and standard deviations.
pac | Compute the proportion above a specific cut location
pac_compare | Compute the difference in the proportion above a specific cut location
pp_plot | Produces the paired probability plot for two groups
seda | Portion of the Stanford Educational Data Archive (SEDA).
star | Data from the Tennessee class size experiment
tpac | Transformed proportion above the cut
tpac_compare | Compare Transformed Proportion Above the Cut
v | Calculate the V effect size statistic