tau2: Variance Components

In donaldRwilliams/blsmeta: Bayesian Location-Scale Meta-Analysis

Description

Typically, the variance components are assumed constant across the k studies in meta-analysis. When scale modeling, the variance components are a function of moderators, which can be computed with this function \insertCite@see @williams2021puttingblsmeta.

Usage

tau2(
  object,
  type = "sd",
  newdata_scale2 = NULL,
  newdata_scale3 = NULL,
  cred = 0.95,
  summary = TRUE,
  digits = 3
)

Arguments

object	An object of class blsmeta.
type	character. Should the variance or standard deviation? The options are type = "var" and type = "sd" (the default).
newdata_scale2	An optional data.frame for which to compute predictions for the level 2 variance component. Defaults to NULL, which then uses the original data used in blsmeta
newdata_scale3	An optional data.frame for which to compute predictions for the level 3 variance component. Defaults to NULL, which then uses the original data used in blsmeta
cred	numeric. credible interval (defaults to 0.95).
summary	logical. Should the posterior samples be summarized (defaults to TRUE)?
digits	numeric. The desired number of digits for the summarized estimates (defaults to 3).

Value

A data frame of predicted values.

References

\insertAllCited

'

Examples

library(psymetadata)

fit <- blsmeta(yi = yi, vi = vi, 
               es_id = es_id,
               mods_scale2 = ~n,
               data = gnambs2020)


tau2(object = fit, 
     newdata_scale2 = data.frame(n = seq(20, 100, 10)))

donaldRwilliams/blsmeta documentation built on Dec. 20, 2021, 12:12 a.m.