NAPBF_onez {NAP} | R Documentation |
Bayes factor in favor of the NAP in one-sample z
tests
Description
In a N(\mu,\sigma_0^2)
population with known variance \sigma_0^2
, consider the two-sided one-sample z
-test for testing the point null hypothesis H_0 : \mu = 0
against H_1 : \mu \neq 0
. Based on an observed data, this function calculates the Bayes factor in favor of H_1
when a normal moment prior is assumed on the standardized effect size \mu/\sigma_0
under the alternative.
Usage
NAPBF_onez(obs, nObs, mean.obs, test.statistic,
tau.NAP = 0.3/sqrt(2), sigma0 = 1)
Arguments
obs |
Numeric vector. Observed vector of data. |
nObs |
Numeric or numeric vector. Sample size(s). Same as |
mean.obs |
Numeric or numeric vector. Sample mean(s). Same as |
test.statistic |
Numeric or numeric vector. Test-statistic value(s). |
tau.NAP |
Positive numeric. Parameter in the moment prior. Default: |
sigma0 |
Positive numeric. Known standard deviation in the population. Default: 1. |
Details
Users can either specify
obs
, ornObs
andmean.obs
, ornObs
andtest.statistic
.If
obs
is provided, it returns the corresponding Bayes factor value.If
nObs
andmean.obs
are provided, the function is vectorized over both arguments. Bayes factor values corresponding to the values therein are returned.If
nObs
andtest.statistic
are provided, the function is vectorized over both arguments. Bayes factor values corresponding to the values therein are returned.
Value
Positive numeric or numeric vector. The Bayes factor value(s).
Author(s)
Sandipan Pramanik and Valen E. Johnson
References
Pramanik, S. and Johnson, V. (2022). Efficient Alternatives for Bayesian Hypothesis Tests in Psychology. Psychological Methods. Just accepted.
Johnson, V. and Rossell, R. (2010). On the use of non-local prior densities in Bayesian hypothesis tests. Journal of the Royal Statistical Society: Series B, 72:143-170. [Article]
Examples
NAPBF_onez(obs = rnorm(100))