pwranova 1.1.5 (2026-07-26)

• Updated citation information following publication in JOSS.
• Added Japanese documentation to the package website.

pwranova 1.1.4 (2026-06-19)

• Fixed an issue in pwranova() where epsilon adjustments were not fully incorporated into noncentrality parameter calculations.
• Expanded validation tests, including additional comparisons with G*Power.

pwranova 1.1.3 (2026-06-18)

• Added conventional effect-size benchmarks based on Cohen (1988) in pwranova(), pwrttest(), and pwrcortest() documentation.
• Clarified the relationship between eta-squared and partial eta squared in pwranova() documentation.

pwranova 1.1.2 (2026-06-18)

• Clarified effect-size definitions and noncentrality parameter calculations in pwrttest() documentation.

pwranova 1.1.1 (2026-03-05)

• Strengthened input validation across functions. Added checks for finite values, parameter bounds, and boundary cases in effect-size conversion utilities and power analysis functions.
• Clarified documentation for pwrcortest() and pwrttest() to state that signed effect-size inputs (rho, delta) are converted to their absolute values.

pwranova 1.1.0 (2026-03-05)

• Added ncp_scale argument to pwrcortest() for alternative scaling of the noncentrality parameter in correlation power analysis.

pwranova 1.0.3 (2026-01-19)

• Fixed a bug in the denominator df for paired/repeated-measures contrast tests.

pwranova 1.0.2 (2025-10-01)

• Minor adjustments in DESCRIPTION and documentation links.
  
• Small fixes in preparation for CRAN submission.

pwranova 1.0.1 (2025-09-30)

• Removed obsolete comments in code.
• Updated citation information.
• Minor updates to DESCRIPTION.

pwranova 1.0.0 (2025-09-28)

• First stable release of the package.

• Provides power analysis functions for:

  • Between-, within-, and mixed-factor ANOVA designs (main effects and interactions).
  • Planned contrasts with user-defined weights.
  • t-tests (one-sample, paired, and two-sample).
  • Pearson correlations (using either the t-distribution or Fisher’s z-transformation).

• Supports solving for:

  • Statistical power
  • Required total sample size
  • Significance level (alpha)
  • Minimal detectable effect size (Cohen’s f, partial eta squared, or Cohen’s d-type indices).

• Validated against G*Power for supported ANOVA designs, t-tests, and correlation tests.