jzs_cor: A default Bayesian hypothesis test for correlation (Wetzels,...

In MicheleNuijten/BayesMed: Default Bayesian Hypothesis Tests for Correlation, Partial Correlation, and Mediation

Description

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).

Usage

jzs_cor(V1, V2,
        alternative = c("two.sided", "less", "greater"),
        n.iter=10000,n.burnin=500,standardize=TRUE, subdivisions = 200)

Arguments

V1	a numeric vector.
V2	a numeric vector of the same length as V1.
alternative	specify the alternative hypothesis for the correlation coefficient: two.sided, greater than zero, or less than zero.
n.iter	number of total iterations per chain (see the package R2jags). Defaults to 10000.
n.burnin	length of burn in, i.e. number of iterations to discard at the beginning(see the package R2jags). Defaults to 500.
standardize	logical. Should the variables be standardized? Defaults to TRUE.
subdivisions	the maximum number of subdivisions. Defaults to 200.

Details

See Wetzels & Wagenmakers (2012).

Value

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.

Author(s)

Michele B. Nuijten <[e-mail]>, Ruud Wetzels, Dora Matzke, Conor V. Dolan, and Eric-Jan Wagenmakers.

References

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.

See Also

jzs_partcor, jzs_med

Examples

## Not run: 
# generate correlational data
X <- rnorm(100)
Y <- .4*X + rnorm(100,0,1)

# run jzs_cor
result <- jzs_cor(X,Y)

# inspect posterior distribution 
plot(result$alpha_samples)

# print a traceplot of the chains
plot(result$jagssamples)


## End(Not run)

MicheleNuijten/BayesMed documentation built on Jan. 31, 2020, 7:45 a.m.