vi
vector of length \(k\) with the corresponding sampling variances. See ‘Details’.
weights
optional argument to specify a vector of length \(k\) with user-defined weights. See ‘Details’.
ai
see below and the documentation of the escalc
function for more details.
bi
see below and the documentation of the escalc
function for more details.
ci
see below and the documentation of the escalc
function for more details.
di
see below and the documentation of the escalc
function for more details.
n1i
see below and the documentation of the escalc
function for more details.
n2i
see below and the documentation of the escalc
function for more details.
x1i
see below and the documentation of the escalc
function for more details.
x2i
see below and the documentation of the escalc
function for more details.
t1i
see below and the documentation of the escalc
function for more details.
t2i
see below and the documentation of the escalc
function for more details.
m1i
see below and the documentation of the escalc
function for more details.
m2i
see below and the documentation of the escalc
function for more details.
sd1i
see below and the documentation of the escalc
function for more details.
sd2i
see below and the documentation of the escalc
function for more details.
xi
see below and the documentation of the escalc
function for more details.
mi
see below and the documentation of the escalc
function for more details.
ri
see below and the documentation of the escalc
function for more details.
ti
see below and the documentation of the escalc
function for more details.
sdi
see below and the documentation of the escalc
function for more details.
r2i
see below and the documentation of the escalc
function for more details.
ni
see below and the documentation of the escalc
function for more details.
mods
optional argument to include one or more moderators in the model. A single moderator can be given as a vector of length \(k\) specifying the values of the moderator. Multiple moderators are specified by giving a matrix with \(k\) rows and as many columns as there are moderator variables. Alternatively, a model formula
can be used to specify the model. See ‘Details’.
measure
character string indicating the type of data supplied to the function. When measure="GEN"
(default), the observed effect sizes or outcomes and corresponding sampling variances (or standard errors) should be supplied to the function via the yi
, vi
, and sei
arguments (only one of the two, vi
or sei
, needs to be specified). Alternatively, one can set measure
to one of the effect size or outcome measures described under the documentation for the escalc
function and specify the needed data via the appropriate arguments.
intercept
logical indicating whether an intercept should be added to the model (the default is TRUE
). Ignored when mods
is a formula.
slab
optional vector with labels for the \(k\) studies.
subset
optional vector indicating the subset of studies that should be used for the analysis. This can be a logical vector of length \(k\) or a numeric vector indicating the indices of the observations to include.
add
see the documentation of the escalc
function.
to
see the documentation of the escalc
function.
drop00
see the documentation of the escalc
function.
vtype
see the documentation of the escalc
function.
method
character string specifying whether a fixed- or a random/mixed-effects model should be fitted. A fixed-effects model (with or without moderators) is fitted when using method="FE"
. Random/mixed-effects models are fitted by setting method
equal to one of the following: "DL"
, "HE"
, "SJ"
, "ML"
, "REML"
, "EB"
, "HS"
, or "GENQ"
. Default is "REML"
. See ‘Details’.
weighted
logical indicating whether weighted (default) or unweighted estimation should be used to fit the model.
test
character string specifying how test statistics and confidence intervals for the fixed effects should be computed. By default (test="z"
), Wald-type tests and CIs are obtained, which are based on a standard normal distribution. When test="knha"
, the method by Knapp and Hartung (2003) is used for adjusting test statistics and confidence intervals. See ‘Details’.
digits
integer specifying the number of decimal places to which the printed results should be rounded (if unspecified, the default is 4).
btt
optional vector of indices specifying which coefficients to include in the omnibus test of moderators. See ‘Details’.
verbose
logical indicating whether output should be generated on the progress of the model fitting (the default is FALSE
). Can also be an integer. Values > 1 generate more verbose output. See ‘Note’.
control
optional list of control values for the iterative estimation algorithms. If unspecified, default values are defined inside the function. See ‘Note’.