A Calculator for Single-Case Effect Sizes

Provides R functions for calculating basic effect size indices for single-case designs, including several non-overlap measures and parametric effect size measures, and for estimating the gradual effects model developed by Swan and Pustejovsky (2018) . Standard errors and confidence intervals (based on the assumption that the outcome measurements are mutually independent) are provided for the subset of effect sizes indices with known sampling distributions.

News

SingleCaseES 0.4.1

Fixed bug in SCD_effect_sizes() shiny app that caused an error in batch calculator when LRRi, LRRd, or LOR were not selected.
calc_ES() now returns a zero-length data frame if condition and outcome arguments are both length-zero vectors.
calc_ES() errors if condition and outcome arguments are not the same length.

SingleCaseES 0.4.0

Added calc_ES() function for calculating multiple effect size estimates on a single data series.
Added batch_calc_ES() function for calculating effect size estimates for multiple data series.
Added gem_scd() function for estimating the gradual effects model (Swan & Pustejovsky, 2018).
Added shiny app for calculating basic within-case effect sizes.
Added shiny app for estimating effect sizes based on gradual effects model.
Revised documentation.
Added unit tests.
Added vignettes.

SingleCaseES 0.3

Fixed definitions of PAND and IRD to handle cases of complete overlap (i.e., where all of the data from a phase must be removed to achieve non-overlap).