Estimating Hierarchical Linear Models for Single-Case Designs R package scdhlm version 0.7.4 Provides a set of tools for estimating hierarchical linear models and effect sizes based on data from single-case designs. Functions are provided for calculating standardized mean difference effect sizes that are directly comparable to standardized mean differences estimated from between-subjects randomized experiments, as described in Hedges, Pustejovsky, and Shadish (2012) <DOI:10.1002/jrsm.1052>; Hedges, Pustejovsky, and Shadish (2013) <DOI:10.1002/jrsm.1086>; Pustejovsky, Hedges, and Shadish (2014) <DOI:10.3102/1076998614547577>; and Chen, Pustejovsky, Klingbeil, and Van Norman (2023) <DOI:10.1016/j.jsp.2023.02.002>. Includes an interactive web interface. Software Depends: nlme, R (>= 3.0.1) Imports: stats, utils, readxl, rlang, dplyr, tidyselect, magrittr, lmeInfo (>= 0.3.0) Suggests: knitr, markdown, rmarkdown, ggplot2, plyr, boot, parallel, shiny, shinytest, glue, janitor, rclipboard, rvest, testthat, snow, doSNOW, foreach, iterators, reshape, rlecuyer James Pustejovsky <jepusto@gmail.com> Comprehensive R Archive Network (CRAN) James Pustejovsky [aut, cre], Man Chen [aut], Bethany Hamilton [aut] GPL-3 2026-01-21 application/tgz https://CRAN.R-project.org/package=scdhlm doi:10.32614/CRAN.package.scdhlm en-US