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Calculate Statistical Power

Source: R/stat.R
stat_power.Rd

Computes statistical power for a planned study given sample size, effect size, and design parameters. Supports t-tests (two-sample, one-sample, paired), ANOVA, proportion tests, correlation tests, and chi-square tests.

Usage

stat_power(
  n,
  effect_size,
  test = c("t_two", "t_one", "t_paired", "anova", "proportion", "correlation", "chisq"),
  alternative = c("two.sided", "less", "greater"),
  alpha = 0.05,
  k = NULL,
  df = NULL
)

# S3 method for class 'power_result'
plot(x, y = NULL, plot_range = NULL, ...)

Arguments

n

Integer. Sample size. Interpretation depends on test:

  • "t_two", "anova": per group

  • "t_paired": number of pairs

  • all others: total

effect_size

Numeric. Effect size appropriate for the chosen test (must be positive). Conventions:

  • Cohen's d for t-tests (small 0.2, medium 0.5, large 0.8)

  • Cohen's f for ANOVA (small 0.1, medium 0.25, large 0.4)

  • Cohen's h for proportion tests (small 0.2, medium 0.5, large 0.8)

  • Pearson r for correlation (small 0.1, medium 0.3, large 0.5)

  • Cohen's w for chi-square (small 0.1, medium 0.3, large 0.5)

test

Character. Test type: "t_two" (two-sample t-test, default), "t_one" (one-sample t-test), "t_paired" (paired t-test), "anova", "proportion", "correlation", or "chisq".

alternative

Character. Direction of the alternative hypothesis: "two.sided" (default), "less", or "greater". Ignored for "anova" and "chisq".

alpha

Numeric. Significance level (Type I error rate). Default: 0.05.

k

Integer \(\ge 2\). Number of groups. Required when test = "anova".

df

Integer \(\ge 1\). Degrees of freedom. Required when test = "chisq".

x

A power_result object returned by stat_power() or stat_n().

y

Ignored.

plot_range

Numeric vector of length 2. Custom axis range for the curve. For stat_power() results: range over sample sizes. For stat_n() results: range over effect sizes. NULL uses an automatic range.

...

Additional arguments (currently unused).

Value

An object of class "power_result" (invisibly) containing:

params

Named list of all input parameters

power

Computed statistical power (numeric in [0, 1])

computed

"power" — distinguishes from stat_n() results where computed = "n"

interpretation

Plain-text interpretation of the power value

recommendation

Actionable recommendation, or NULL when power is between 0.8 and 0.95

Use print(result) for a brief summary, summary(result) for full details, and plot(result) to display the power curve.

Examples

if (FALSE) { # \dontrun{
result <- stat_power(n = 30, effect_size = 0.5)
print(result)
summary(result)
plot(result)

stat_power(n = 25, effect_size = 0.25, test = "anova", k = 3)
stat_power(n = 50, effect_size = 0.3,  test = "correlation",
           alternative = "greater")
} # }