Firefighters: Data from a study of health promotion of firefighters

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

Description

Data from a study of health promotion of firefighters (Elliot et al., 2007). These data are also used as an example in the Bayesian mediation paper of Yuan and MacKinnon (2009) and Nuijten et al. (2014).

Usage

data(Firefighters)

Format

A data frame with 354 observations on the following 3 variables.

y

Dependent variable: reported eating of fruits and vegetables

m

Mediating variable: change from baseline to followup in knowledge of the benefits of eating fruits and vegetables

x

Independent variable: randomized exposure to an intervention

Details

The data are centered.

Source

Elliot, D. L., Goldberg, L., Kuehl, K. S., Moe, E. L., Breger, R. K. R., Pickering, M. A. (2007). The PHLAME (Promoting Healthy Lifestyles: Alternative Models' Effects) Firefighter Study: Outcomes of Two Models of Behavior Change. JOEM, 49, 204-213.

References

Elliot, D. L., Goldberg, L., Kuehl, K. S., Moe, E. L., Breger, R. K. R., Pickering, M. A. (2007). The PHLAME (Promoting Healthy Lifestyles: Alternative Models' Effects) Firefighter Study: Outcomes of Two Models of Behavior Change. JOEM, 49, 204-213.

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

Yuan, Y., & MacKinnon, D. (2009). Bayesian mediation analysis. Psychological Methods, 14 , 301-322.

Examples

## Not run: 
data(Firefighters)

# mediation analysis
result <- jzs_med(Firefighters$x,Firefighters$y,Firefighters$m)
result

### Note that the Bayes factor is 1.96, instead of 1.94 as reported 
### in the paper (Nuijten et al., 2014). 
### This is caused by rounding differences; the posterior probabilities are equal.

# underlying mediational model with path weights and posterior probabilities
plot(result$main_result)

# posterior distribution of indirect effect "ab" incl 95% credible interval
plot(result$ab_samples)

## End(Not run)

BayesMed documentation built on May 2, 2019, 9:27 a.m.