Description Usage Arguments Value Warning Author(s) References See Also Examples
This function can be used to perform a default Bayesian hypothesis test for correlation, using the Savage-Dickey method (Dickey & Lientz, 1970). The test uses a Jeffreys-Zellner-Siow prior set-up (Liang et al., 2008).
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V1 |
a numeric vector. |
V2 |
a numeric vector of the same length as V1. |
SDmethod |
specify the precise method with which the density of the posterior distribution will be estimated in order to compute the Savage-Dickey ratio. |
alternative |
specify the alternative hypothesis for the correlation coefficient: |
n.iter |
number of total iterations per chain (see the package |
n.burnin |
length of burn in, i.e. number of iterations to discard at the beginning(see the package |
standardize |
logical. Should the variables be standardized? Defaults to TRUE. |
A list containing the following components:
Correlation |
The correlation coefficient for the relation between V1 and V2. The correlation coefficient is calculated by standardizing the mean of the posterior samples: mean(samples)*(sd(V1)/sd(V2)). |
BayesFactor |
The Bayes factor for the correlation coefficient. A value greater than one indicates evidence in favor of correlation, a value smaller than one indicates evidence against correlation. |
PosteriorProbability |
The posterior probability for the existence of a correlation between V1 and V2. |
alpha |
The posterior samples for the correlation coefficient alpha. |
jagssamples |
The JAGS output for the MCMC estimation of the path. This object can be used to construct a traceplot. |
In some cases the SDmethod fit.st
will fail to converge. If so, another optimization method is used, using different starting values. If the other optimization method does not converge either or gives you a negative Bayes factor (which is meaningless), you could try one of the other SDmethod options or see jzs_cor
.
Michele B. Nuijten <m.b.nuijten@uvt.nl>, Ruud Wetzels, Dora Matzke, Conor V. Dolan, and Eric-Jan Wagenmakers.
Dickey, J. M., & Lientz, B. P. (1970). The weighted likelihood ratio, sharp hypotheses about chances, the order of a Markov chain. The Annals of Mathematical Statistics, 214-226.
Liang, F., Paulo, R., Molina, G., Clyde, M. A., & Berger, J. O. (2008). Mixtures of g priors for Bayesian variable selection. Journal of the American Statistical Association, 103(481), 410-423.
Nuijten, M. B., Wetzels, R., Matzke, D., Dolan, C. V., & Wagenmakers, E.-J. (2014). A default Bayesian hypothesis test for mediation. Behavior Research Methods. doi: 10.3758/s13428-014-0470-2
Wetzels, R., & Wagenmakers, E.-J. (2012). A Default Bayesian Hypothesis Test for Correlations and Partial Correlations. Psychonomic Bulletin & Review, 19, 1057-1064.
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