ftestEvidence {JustifyAlpha}

Justify your alpha level by avoiding the Lindley paradox or aiming for moderate or strong evidence when using anova.

Description

Justify your alpha level by avoiding the Lindley paradox or aiming for moderate or strong evidence when using anova.

Usage

ftestEvidence(evidence, df1, df2, paired = FALSE, printplot = FALSE)

Arguments

evidence

Desired level of evidence: "Lindley" to avoid the Lindley Paradox, "moderate" to achieve moderate evidence and "strong" to achieve strong evidence. Users that are more familiar with Bayesian statistics can also directly enter their desired Bayes factor.

df1

Numerator degrees of freedom.

df2

Denominator degrees of freedom.

paired

If true a within subjects design is assumed.

printplot

If true prints a plot relating Bayes factors and p-values.

Value

numeric alpha level required to avoid Lindley's paradox.

References

Maier & Lakens (2021). Justify Your Alpha: A Primer on Two Practical Approaches

Examples

## Avoid the Lindley paradox for an anova with 1 numerator and 248 denominator degrees of freedom.
ftestEvidence("lindley", 1, 248)