# Visualization and Estimation of Effect Sizes

## Documentation for package ‘esvis’ version 0.2.0

- DESCRIPTION file.

## Help Pages

auc | Calculate the area under the curve
benchmarks | Synthetic benchmark screening data
binned_plot | Quantile-binned effect size plot
cdfs | Compute the empirical distribution functions for each of several groups.
coh_d | Compute Cohen's _d_
col_hue | Color hues
col_scheme | Determine the color scheme to be used for the plotting
create_base_legend | Create a base legend for a plot
create_cut_refs | Create a set of reference lines according to a cut score
create_legend | Create a legend for a plot
create_vec | Create a named vector of all possible combinations
ecdf_plot | Empirical Cumulative Distribution Plot
empty_plot | Create an empty 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
parse_form | Parse formula
pooled_sd | Compute pooled standard deviation
pp_annotate | Annotation function to add AUC/V to a given plot
pp_calcs | Produce calculations necessary for pp_plot.
pp_plot | Produces the paired probability plot for two groups
probs | Compute probabilities from the empirical CDFs of a grouping variable for each group.
qtile_es | Compute effect sizes by quantile bins
qtile_mean_diffs | Compute mean differences by various quantiles
qtile_n | Compute sample size for each quantile bin for each group
seda | Portion of the Stanford Educational Data Archive (SEDA).
seg_match | Match segments on a plot
star | Data from the Tennessee class size experiment
themes | Theme settings
tpac | Transformed proportion above the cut
v | Calculate the V effect size statistic