• Revisions to shiny app:
    • The centering, initial treatment time, and follow-up time sliders now only appear when they are relevant.
    • More informative labels for the baseline trend and treatment phase trend options.
  • Fixed a bug so that shine_scd() can take a tibble in the dataset argument.
  • Fixed bug in graph_SCD() function that occurred in treatment reversal designs with cases that had varying numbers of reversals.
  • Fixed bug in shiny app occurring when filtering variable(s) of the input data set.

  • Updated shiny app to clean the variable names of the input data.

  • Modified the Schutte example dataset to exclude the fourth case, for consistency with the analysis presented in Pustejovsky, Hedges, & Shadish (2014).

  • Revised the definition of the treatment-by-time interaction variable calculated in preprocess_SCD() and in the shiny app, for consistency with Pustejovsky, Hedges, & Shadish (2014).

  • Added a new function preprocess_SCD() which handles initial data-cleaning steps for multiple baseline and treatment reversal designs.

  • The scdhlm Shiny app now includes a tab with R code for replicating the app calculations.

  • Imported g_mlm() from lmeInfo.

  • Updated vignette using g_mlm().

  • Updated README using g_mlm().

  • Updated shiny app using g_mlm().

  • Imported extract_varcomp() from lmeInfo. This function extracts variance components from a fitted lme model, which can then be used for g_mlm().

  • Updated CI_g() to allow calculating symmetric and asymmetric confidence intervals for g_HPS objects, g_REML objects, and g_mlm() objects. Note that symmetric confidence interval is the default.

  • Updated HPS estimation functions to work with datasets (issue #2 from austinj).

  • Added additional example datasets (Ruiz, Salazar, Thiemann2001, Thiemann2004, Bryant2018).

  • Updated web-app to allow use of .xlsx files.

  • Fixed bug in web-app occurring when cases were listed out of alphabetical order.

  • Fixed bug in web-app occurring when auto-correlation is very weakly identified.

  • Updated shiny app with additional documentation.

  • Added additional example datasets (BartonArwood, Rodriguez, Romaniuk, AlberMorgan).

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

  • Added vignette demonstrating use of g_REML.
  • Initial release.