Standalone P-Value Interpreter

Usage

interpret_p(p, alpha = 0.05, context = NULL)

Arguments

p: A numeric p-value between 0 and 1
alpha: Significance level. Default 0.05
context: Optional string describing the test context

Value

An object of class statease_pvalue containing the p-value interpretation. Use print() to display the report.

Examples

result <- interpret_p(0.03)
print(result)
#> 
#> -- statease P-Value Interpretation ------------------------------
#>   P-value      : 0.0300
#>   Alpha        : 0.05
#> -----------------------------------------------------------------
#>   Decision     : REJECT the null hypothesis at alpha = 0.05
#>   Evidence     : There is moderate evidence against the null hypothesis.
#> -----------------------------------------------------------------
#>   Interpretation:
#>   The result is statistically significant. The observed data is unlikely to have occurred by chance if the null hypothesis were true.
#> 
#>   Note: Statistical significance does not imply practical importance. Always consider effect size alongside the p-value.
#> -----------------------------------------------------------------
#> 

result2 <- interpret_p(0.12, alpha = 0.05, context = "treatment vs control")
print(result2)
#> 
#> -- statease P-Value Interpretation ------------------------------
#>   Context      : treatment vs control
#>   P-value      : 0.1200
#>   Alpha        : 0.05
#> -----------------------------------------------------------------
#>   Decision     : FAIL TO REJECT the null hypothesis at alpha = 0.05
#>   Evidence     : There is little to no evidence against the null hypothesis.
#> -----------------------------------------------------------------
#>   Interpretation:
#>   The result is not statistically significant. The observed data does not provide sufficient evidence to reject the null hypothesis.
#> 
#>   Note: A non-significant result does not prove the null hypothesis. It may reflect insufficient power or a small sample size.
#> -----------------------------------------------------------------
#>