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NEWS

Updated Tue Dec 07 2021

Superpower 0.2.0 – “Green Lantern”

• Added power_oneway_ancova & power_con_ancova to allow for a basic power analysis of an analysis of covariance (ANCOVA) for one-way, between group designs.
• Added ANCOVA_analytic and ANCOVA_contrast which allow for power analyses for factorial designs and user specified contrasts.
• Added the label_list argument to ANOVA_design and ANCOVA_analytic functions. Now labels can be assigned to factors and levels in a more sane fashion using named lists.

Superpower 0.1.2 – “Rex Splode”

• Minor fixes to power_standardized_alpha to keep Superpower on CRAN

Superpower 0.1.1 – “Black Canary”

• Added morey_plot functions.
  • Plot the effect size (x-axis) at different sample sizes (facets) and at different alpha levels (color).
  • These plots are helpful in determining the sensitivity of statistical tests (t-test and F-test) across a range of effect sizes.
• Added confint method for ANOVA_power produced objects
  • Calculates confidence level for binomial proportion (# of results that are below alpha level) confidence intervals (Wilson, 1927)).
• Minor changes to Shiny apps to fix glitches.

Superpower 0.1.0

• Added ANOVA_exact2 function as an extension of ANOVA_exact
  • Now functional across all sample sizes but does not return a dataframe of afex aov object
• liberal_lambda argument added: allows users to specify the type of lambda calculations
  • When liberal_lambda = TRUE; lambda = cohen_f^2 * (num_df + den_df + 1)
  • When liberal_lambda = FALSE; lambda = cohen_f^2 * den_df
• Optimal alpha functions from JustifieR package added
• ANOVA_compromise function added which allows a compromise power analysis to be performed for all comparisons in a design
• ANOVA_design now returns as a class “design_aov” with specific print and plot methods see ?design_aov-methods
  • generate_cor_matrix function is now a non-exported function within the package (no longer contained within ANOVA_design)
• All simulation functions ANOVA_power, ANOVA_exact, and ANOVA_exact2 now returns as a class “sim_result” with specific print and plot methods see ?sim_result-methods
• plot_power now has reduced sample size limitations -Option to use ANOVA_exact2 (exact2 argument) improves functionality (not limited to product of factors)
• Updated vignettes to include updated information on functions
  • New vignette “Introduction to Justifying Alpha Levels”
• New Shiny App: justify
  • Creates a UI for utilizing the ANOVA_compromise function via Shiny

Superpower 0.0.5

• Superpower_options(“plot”) is now set to TRUE. Plots will, by default, be printed -Easily reset with Superpower_options(plot = FALSE)
• plot_power has new features -Plots now show desired power -min_n is now limited; smallest min_n allowed is equal to the product of the design (e.g., ’2b*2b’ has a smallest min_n of 4)
• Small update to plot_power to fix minor error in original code -Error resulted in power estimates being ~0.1-0.5% off actual power estimate

Superpower 0.0.4

• Added emmeans_power function
  • Documentation added to the vignette
• Small updates to the Shiny apps to fix typos

Superpower 0.0.3

• Unequal sample size in the design is now permitted -Limited to the ANOVA_design and ANOVA_power functions

• Added estimated marginal means comparisons using emmeans R package.

  • emm = TRUE in the ANOVA_power, ANOVA_exact, and plot_power will result in emmeans being calculated
  • Default is all pairwise comparisons but this can be modified with contrast_type and emm_comp options

• Added global options

  • Options that have crossover between functions can now be set globally for the package
  • Includes: verbose, emm, emm_model, contrast_type, alpha_level, and plot
  • These global options can be seen with Superpower_options()

• Updated Shiny Apps

  • Unequal n allowed for ANOVA_power
  • Added numeric input for alpha level (no longer slider)
  • Now includes emmeans options
  • kableExtra, emmeans, magrittr, and dplyr packages now needed to knit markdown file in app.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.