ma_generic: Bare-bones meta-analysis of generic effect sizes

In jadahlke/psychmeta: Psychometric Meta-Analysis Toolkit

Bare-bones meta-analysis of generic effect sizes

Description

This function computes bare-bones meta-analyses of any effect size using user-supplied effect error variances.

Usage

ma_generic(
  es,
  n,
  var_e,
  sample_id = NULL,
  citekey = NULL,
  construct_x = NULL,
  construct_y = NULL,
  group1 = NULL,
  group2 = NULL,
  wt_type = c("sample_size", "inv_var", "DL", "HE", "HS", "SJ", "ML", "REML", "EB", "PM"),
  moderators = NULL,
  cat_moderators = TRUE,
  moderator_type = c("simple", "hierarchical", "none"),
  data = NULL,
  control = control_psychmeta(),
  weights = NULL,
  ...
)

Arguments

es	Vector or column name of observed effect sizes.
n	Vector or column name of sample sizes.
var_e	Vector or column name of error variances.
sample_id	Optional vector of identification labels for samples/studies in the meta-analysis.
citekey	Optional vector of bibliographic citation keys for samples/studies in the meta-analysis (if multiple citekeys pertain to a given effect size, combine them into a single string entry with comma delimiters (e.g., "citkey1,citekey2"). When TRUE, program will use sample-size weights, error variances estimated from the mean effect size, maximum likelihood variances, and normal-distribution confidence and credibility intervals.
construct_x, construct_y	Vector of construct names for constructs designated as "X" and as "Y".
group1, group2	Vector of groups' names associated with effect sizes that represent pairwise contrasts.
wt_type	Type of weight to use in the meta-analysis: native options are "sample_size" and "inv_var" (inverse error variance). Supported options borrowed from metafor are "DL", "HE", "HS", "SJ", "ML", "REML", "EB", and "PM" (see metafor documentation for details about the metafor methods).
moderators	Matrix of moderator variables to be used in the meta-analysis (can be a vector in the case of one moderator).
cat_moderators	Logical scalar or vector identifying whether variables in the moderators argument are categorical variables (TRUE) or continuous variables (FALSE).
moderator_type	Type of moderator analysis ("none", "simple", or "hierarchical").
data	Data frame containing columns whose names may be provided as arguments to vector arguments and/or moderators.
control	Output from the control_psychmeta() function or a list of arguments controlled by the control_psychmeta() function. Ellipsis arguments will be screened for internal inclusion in control.
weights	Optional vector of weights to be used. When weights is non-NULL, these weights override the argument supplied to wt_type.
...	Further arguments to be passed to functions called within the meta-analysis.

Value

A nested tabular object of the class "ma_psychmeta".

Examples

es <- c(.3, .5, .8)
n <- c(100, 200, 150)
var_e <- 1 / n
ma_obj <- ma_generic(es = es, n = n, var_e = var_e)
ma_obj
summary(ma_obj)

jadahlke/psychmeta documentation built on Feb. 11, 2024, 9:15 p.m.