posterior_d: Samples from the posterior distribution of the standardized...

In jbiesanz/fabs: Functions for Applied Behavioural Sciences

Samples from the posterior distribution of the standardized mean difference. The posterior distribution is generated using Fisher's fiducial approach and corresponds exactly to the use of a Jeffrey's prior. Assumes fixed predictor.

Description

Samples from the posterior distribution of the standardized mean difference. The posterior distribution is generated using Fisher's fiducial approach and corresponds exactly to the use of a Jeffrey's prior. Assumes fixed predictor.

Usage

posterior_d(d, n1, n2, filter = 0, upper_null = 0, ndraws = 2e+05)

Arguments

d	The observed standardized mean difference of the previous study based on a pooled standard deviation.
n1	The number of observations in the first group.
n2	The number of observations in the second group.
filter	The filter value reflects the probability of nonsignificant results being filtered. filter = 0 means that there is no filtering and you would have observed nonsignificant results. filter = 1 means that only significant results are observed and you would never have seen nonsigificant results if they had occurred. Filtering is based on alpha = .05 and assumes that are have observed a significant result. Filtering is conducted by weighting (actually filtering) the posterior distribution. For instance, if filter = 1, then the posterior of the null (i.e., the noncentrality parameter is 0) is up to 20 times more likely than when the noncentrality parameter is very large. Setting filter > 0 slows estimation.
upper_null	Specifies the upper value of the composite null hypothesis in units of Cohen's f. The default value of upper_null = 0 keeps the point null hypothesis. A value of, for instance, upper_null = .05 would remove all posterior values between -.05 and .05.
ndraws	Specifies the number of initial samples from the posterior. For small effect sizes and when filter or upper_null > 0 the number of returned samples from the posterior distribution will be lower than ndraws.

Value

A vector of samples from the posterior distribution in units of Cohen's f.

jbiesanz/fabs documentation built on July 15, 2022, 11:02 p.m.