meta_default: Defaults for Model Averaging in Meta-Analysis

Description

Wrapper with default prior for Bayesian meta-analysis based on a literature review. Currently, the same default is used in all cases.

Usage

meta_default(y, SE, labels, data, field = "psychology", effect = "d",
  ...)

Arguments

effect size per study. Can be provided as (1) a numeric vector, (2) the quoted or unquoted name of the variable in data, or (3) a formula to include discrete or continuous moderator variables.

standard error of effect size for each study. Can be a numeric vector or the quoted or unquoted name of the variable in data

labels

optional: character values with study labels. Can be a character vector or the quoted or unquoted name of the variable in data

data

data frame containing the variables for effect size y, standard error SE, labels, and moderators per study.

field

either"psychology" or "medicine" (uses partial matching, so "p" and ""m" are sufficient)

effect

the type of effect size: either Cohen's d ("d"), Pearson correlations ("r"), Fisher's z-transformed correlations ("z"), or log-odds ratios ("logOR").

...

further arguments passed to meta_bma

Details

Default prior distributions can be plotted using plot_default.

For field = "psychology", the following defaults are used:

effect = "d": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.
effect = "r": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.
effect = "z": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.
effect = "logOR": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.

For field = "medicine", the following defaults are used:

effect = "d": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.
effect = "r": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.
effect = "z": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.
effect = "logOR": Half-normal with SD=0.3 on mean effect and half-Cauchy with scale=.5 on standard deviation of effects.

References

Gronau, Q. F., Erp, S. V., Heck, D. W., Cesario, J., Jonas, K. J., & Wagenmakers, E.-J. (2017). A Bayesian model-averaged meta-analysis of the power pose effect with informed and default priors: the case of felt power. Comprehensive Results in Social Psychology, 2(1), 123-138. https://doi.org/10.1080/23743603.2017.1326760

Examples

Run this code

# NOT RUN {
# Note: The following example optimizes speed (for CRAN checks).
#       The settings are not suitable for actual data analysis!

data(towels)
set.seed(123)
md <- meta_default(logOR, SE, study, towels,
                   field = "psych", effect = "logOR",
                   rel.tol=.Machine$double.eps^.15, iter=1000)
md
plot_forest(md)
# }