# Eq_Testing: Bayesian Equivalence Testing for Cohen's d in t-test Designs In rnorouzian/BayesianforL2: Introduction to Bayesian Thinking for L2 Researchers

## Description

Provides complete results of Bayesian Equivalence Testing with an "additional function" showing the result of changing the equivalence bounds to any different sizes.

## Usage

 `1` ```Eq_Testing(t, N1, N2, wid = "wi", dL = -.1, dU = .1) ```

## Arguments

 `t` The observed t-value. `N1` Group 1 sample size. `N2` Group 2 sample size (if a two-sample design). `wid` Width or Scale of a Cauchy prior. `dL` Lower limit of equivalence bound for d. `dU` Upper limit of equivalence bound for d.

## Details

Equivalnce Testing simply presents another alternative to absolute hypotheis testing (i.e., testing whether an effect is excatly 0). Specifically, we allow a bound of values which in our view are practically equivalent to zero to be our null hypothesis (i.e., a composite Null). However, most Bayeian point decisions are better decided upon using a "Decision-Theoritic" approch (see, Berger, 1985).

## Value

Provides complete results of Bayesian Equivalence Testing using High Desity Region (HDI) with an "additional function" showing the result of changing the equivalence bounds to any different sizes.

## Author(s)

Reza Norouzian <rnorouzian@gmail.com>

## Examples

 ```1 2 3 4 5 6``` ```# Suppose a researcher obtains a t-value of 1, from 2 groups each with 20 participants. # The researcher picks a "wi", wide, Cauchy prior. The researcher uses # dL of -0.1 and dU of 0.1 to see the result of equivalene testing: Eq_Testing(t = 1, N1 = 20, N2 = 20, dL = -.1, dU = .1 ) ```

rnorouzian/BayesianforL2 documentation built on May 29, 2019, 8:37 a.m.