Contains several functions for equivalence testing and practical significance testing. First, the tsti() command provides an automatic computation of three-sided testing results for a given estimate, standard error, and region of practical equivalence. For details, see Goeman, Solari, & Stijnen (2010) <doi:10.1002/sim.4002> and Isager & Fitzgerald (2024) <doi:10.31234/osf.io/8y925>. Second, the lddtest() command performs logarithmic density discontinuity equivalence testing for regression discontinuity designs. For reference, see Fitzgerald (2025) <doi:10.31222/osf.io/2dgrp_v1>.

Support functions for R-based "EQUALCompareImages - Compare similarity between and within images" shiny application which allow researchers without coding skills or expertise in image comparison algorithms to compare images. Gurusamy,K (2025)<doi:10.5281/zenodo.16994047>.

Tests the equality of two covariance matrices, used in paper "Two sample tests for high dimensional covariance matrices." Li and Chen (2012) <arXiv:1206.0917>.

The equality of a large number k of densities is tested by measuring the L2 distance between the corresponding kernel density estimators and the one based on the pooled sample. The test even works for sample sizes as small as 2.

Support functions for R-based "EQUALencrypt - Encrypt and decrypt whole files" and "EQUALencrypt - Encrypt and decrypt columns of data" shiny applications which allow researchers without coding skills or expertise in encryption algorithms to share data after encryption. Gurusamy,K (2025)<doi:10.5281/zenodo.16743676> and Gurusamy,K (2025)<doi:10.5281/zenodo.16744058>.

Support functions for R-based 'EQUAL-STATS' software which automatically classifies the data and performs appropriate statistical tests. 'EQUAL-STATS' software is a shiny application with an user-friendly interface to perform complex statistical analysis. Gurusamy,K (2024)<doi:10.5281/zenodo.13354162>.

Functions for examining measurement invariance via equivalence testing are included in this package. The traditionally used RMSEA (Root Mean Square Error of Approximation) cutoff values are adjusted based on simulation results. In addition, a projection-based method is implemented to test the equality of latent factor means across groups without assuming the equality of intercepts. For more information, see Yuan, K. H., & Chan, W. (2016) <doi:10.1037/met0000080>, Deng, L., & Yuan, K. H. (2016) <doi:10.1007/s11336-015-9491-8>, and Jiang, G., Mai, Y., & Yuan, K. H. (2017) <doi:10.3389/fpsyg.2017.01823>.