Description Usage Arguments Details Value Author(s) References See Also Examples

This function can be used to perform a default Bayesian hypothesis test for correlation, using 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. |

`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. |

See Wetzels & Wagenmakers (2012).

The function returns a list with the following items:

`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. |

Michele B. Nuijten <m.b.nuijten@uvt.nl>, Ruud Wetzels, Dora Matzke, Conor V. Dolan, and Eric-Jan Wagenmakers.

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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