Function reference • SingleCaseES

Calculating one or more effect size estimates Functions for calculating one or more effect size estimates.
`batch_calc_ES()`	Calculate effect sizes from a dataset for multiple series
`calc_ES()`	Calculate effect sizes
`calc_phase_pairs()`	Calculate phase pair numbers
Calculating non-overlap effect size indices Functions for calculating non-overlap effect size indices for single-case designs.
`IRD()`	Robust improvement rate difference
`NAP()`	Non-overlap of all pairs
`PAND()`	Percentage of all non-overlapping data (PAND)
`PEM()`	Percentage exceeding the median
`PND()`	Percentage of non-overlapping data
`Tau()`	Tau (non-overlap)
`Tau_BC()`	Tau-BC
`Tau_U()`	Tau-U
Calculating parametric effect size indices Functions for calculating parametric effect size indices for single-case designs.
`LRRd()` `LRRi()`	Log-response ratio
`LRRd()` `LRRi()`	Log-response ratio
`LOR()`	Log-odds ratio
`LRM()`	Log ratio of medians
`SMD()`	Within-case standardized mean difference
Estimating the gradual effects model Function for estimating the gradual effects model for single-case designs
`gem_scd()`	A function to estimate the gradual effects model for an SCD
Shiny App Function to launch shiny app
`SCD_effect_sizes()`	SCD effect size calculator
`shine_gem_scd()`	Gradual Effects Model SCD Calculator
Example Datasets Example datasets from single-case designs
`McKissick`	McKissick et al. (2010)
`Schmidt2007`	Schmidt (2007)
`Schmidt2012`	Schmidt and Stichter (2012)
`Shogren`	Shogren et al. (2004)
`Thorne`	Thorne and Kamps (2008)
`Wright2012`	Wright & McCathren (2012)

Reference

Calculating one or more effect size estimates

Calculating non-overlap effect size indices

Calculating parametric effect size indices

Estimating the gradual effects model

Shiny App

Example Datasets