Description: Parametric and nonparametric statistics for single-case design. Regarding nonparametric statistics, the index suggested by Parker, Vannest, Davis and Sauber (2011) <doi:10.1016/j.beth.2010.08.006> was included. It combines both nonoverlap and trend to estimate the effect size of a treatment in a single case design.

Title: The Causal Effects for a Causal Loglinear Model
Description: Fitting a causal loglinear model and calculating the causal effects for a causal loglinear model with the multiplicative interaction or without the multiplicative interaction, obtaining the natural direct, indirect and the total effect. It calculates also the cell effect, which is a new interaction effect.

Title: Functions for computing effect sizes
Description: This package contains the functions to compute standardized

Title: Efficient effects size computation
Description: This package contains the functions to compute the standardized
effect sizes for experiments (Cohen d, Hedges g, Cliff delta).

Title: Efficient effect size computation
effect sizes for experiments (Cohen d, Hedges g, Cliff delta, Vargha and Delaney A).
The computation algorithms have been optimized to allow efficient computation even

Title: Efficient Effect Size Computation
Authors@R: c(person("Marco", "Torchiano", role = c("aut", "cre"),
Description: A collection of functions to compute the standardized
effect sizes for experiments (Cohen d, Hedges g, Cliff delta, Vargha-Delaney A).

Title: Efficient Fitting of Linear and Generalized Linear Models
Description: Efficient Fitting of Linear and Generalized Linear Models by using
just base R. As an alternative to lm() and glm(), this package provides elm()
and eglm(), with a significant speedup when the number of
observations is larger than the number of parameters to estimate, as it
reduces the NxP model matrix to a PxP matrix. The best computational
performance is obtained when R is linked against 'OpenBLAS', 'Intel MKL' or
other optimized 'BLAS' library. This implementation aims at being compatible
with 'broom' and 'sandwich' packages for summary statistics and clustering by
Imports: stats, zoo, methods, utils, vctrs
Suggests: testthat (>= 3.0.0), covr, sandwich, MASS, tibble, broom