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.

1 2 3 4 5 6 7 | ```
# 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)
``` |

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