Post_Cohen_d: Bayesian Estimation and Model Selection for Cohen's d in...
In rnorouzian/BayesianforL2: Introduction to Bayesian Thinking for L2 Researchers

Description Usage Arguments Value Author(s) See Also Examples

Provides complete Summary of Posterior, and Hypothesis Testing Results (i.e., Bayes Factors).

1	Post_Cohen_d(t, N1, N2 = NULL, tl = 2, ttype, dexp = 1, wid = "wi")

`t`	Observed t value.
`N1`	Group 1 sample size.
`N2`	Group 2 sample size (if a two-sample design).
`tl`	Type of Hypothesis.
`ttype`	Type of t test.
`dexp`	Expected direction of Cohens d before doing the study.
`wid`	Width or Scale of a Cauchy prior.

Provides graphical as well as full textual description of posterior distribution of effect size. Additionally, does Bayesian hypothesis testing producing Bayes Factors.

Reza Norouzian <rnorouzian@gmail.com>

https://rezanorouzian.shinyapps.io/bayes-t/ for an interactive and more powerful version of this function which also compares the frequentist and the Bayesian results with each other.

# Suppose a researcher obtains a t value of 1, from 2 groups each with 20 participants.
# Thus, ttype is 2. The researcher picks a "wi", wide, Cauchy prior. Suppose
# researcher has no prefernce for the direction of Cohen d. Thus, tl 2.
# when hypothesis is two tailed, dexp is ignored. The researcher can use:


# Post_Cohen_d(t = .5, N1 = 20, ttype = 1)

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