Parametric, non-parametric, robust, and Bayesian random-effects meta-analysis.
meta_analysis(
data,
type = "parametric",
random = "mixture",
digits = 2L,
conf.level = 0.95,
...
)The returned tibble data frame can contain some or all of the following columns (the exact columns will depend on the statistical test):
statistic: the numeric value of a statistic
df: the numeric value of a parameter being modeled (often degrees
of freedom for the test)
df.error and df: relevant only if the statistic in question has
two degrees of freedom (e.g. anova)
p.value: the two-sided p-value associated with the observed statistic
method: the name of the inferential statistical test
estimate: estimated value of the effect size
conf.low: lower bound for the effect size estimate
conf.high: upper bound for the effect size estimate
conf.level: width of the confidence interval
conf.method: method used to compute confidence interval
conf.distribution: statistical distribution for the effect
effectsize: the name of the effect size
n.obs: number of observations
expression: pre-formatted expression containing statistical details
For examples, see data frame output vignette.
A data frame. It must contain columns named estimate (effect
sizes or outcomes) and std.error (corresponding standard errors). These
two columns will be used:
as yi and sei arguments in metafor::rma() (for parametric test)
as yi and sei arguments in metaplus::metaplus() (for robust test)
as y and SE arguments in metaBMA::meta_random() (for Bayesian test)
A character specifying the type of statistical approach:
"parametric"
"nonparametric"
"robust"
"bayes"
You can specify just the initial letter.
The type of random effects distribution. One of "normal", "t-dist", "mixture", for standard normal, \(t\)-distribution or mixture of normals respectively.
Number of digits for rounding or significant figures. May also
be "signif" to return significant figures or "scientific"
to return scientific notation. Control the number of digits by adding the
value as suffix, e.g. digits = "scientific4" to have scientific
notation with 4 decimal places, or digits = "signif5" for 5
significant figures (see also signif()).
Scalar between 0 and 1 (default: 95%
confidence/credible intervals, 0.95). If NULL, no confidence intervals
will be computed.
Additional arguments passed to the respective meta-analysis function.
The table below provides summary about:
statistical test carried out for inferential statistics
type of effect size estimate and a measure of uncertainty for this estimate
functions used internally to compute these details
Hypothesis testing and Effect size estimation
| Type | Test | CI available? | Function used |
| Parametric | Pearson's correlation coefficient | Yes | correlation::correlation() |
| Non-parametric | Spearman's rank correlation coefficient | Yes | correlation::correlation() |
| Robust | Winsorized Pearson's correlation coefficient | Yes | correlation::correlation() |
| Bayesian | Bayesian Pearson's correlation coefficient | Yes | correlation::correlation() |
Patil, I., (2021). statsExpressions: R Package for Tidy Dataframes and Expressions with Statistical Details. Journal of Open Source Software, 6(61), 3236, https://doi.org/10.21105/joss.03236