Estimating Hierarchical Linear Models for Single-Case Designs

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) ; Hedges, Pustejovsky, and Shadish (2013) ; and Pustejovsky, Hedges, and Shadish (2014) . Includes an interactive web interface.


scdhlm 0.3.1

  • updated shiny app with additional documentation
  • added additional example datasets (BartonArwood, Rodriguez, Romaniuk)

scdhlm 0.3

  • shiny app for calculating between-case standardized mean difference effect sizes.

scdhlm 0.2.2

  • Bug fix in lme_AR1_cov_block_inv.
  • Fixed bug in HPS effect size functions so that results are not dependent on order of data.

scdhlm 0.2.1

  • Added vignette demonstrating use of g_REML.

scdhlm 0.2

  • Initial release.

Reference manual

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0.3.1 by James Pustejovsky, 2 months ago

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Browse source code at

Authors: James Pustejovsky [aut, cre]

Documentation:   PDF Manual  

GPL-3 license

Imports stats

Depends on nlme

Suggests knitr, markdown, rmarkdown, ggplot2, plyr, boot, parallel, shiny, testthat

See at CRAN