ttestEvidence: Justify your alpha level by avoiding the Lindley paradox or...

In JustifyAlpha: Justifying Alpha Levels for Hypothesis Tests

Description

Justify your alpha level by avoiding the Lindley paradox or aiming for moderate or strong evidence when using a t-test.

Usage

ttestEvidence(
  evidence,
  n1,
  n2 = 0,
  one.sided = FALSE,
  rscale = sqrt(2)/2,
  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.
n1	Sample size in Group 1.
n2	Sample size in Group 2. Leave blank for a one-sample or paired-sample
one.sided	Indicates whether the test is one sided or two sided.
rscale	Scale of the Cauchy prior
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 a two sample t-test with 300 participants per condition
ttestEvidence("lindley", 300, 300)

JustifyAlpha documentation built on Sept. 15, 2021, 9:08 a.m.