This function computes Wald-type pairwise comparisons for each level of
categorical moderators for an ma_psychmeta
object, as well as an ombnibus
one-way ANOVA test (equal variance not assumed).
Currently, samples across moderator levels are assumed to be independent.
# S3 method for ma_psychmeta
anova(
object,
...,
analyses = "all",
moderators = NULL,
L = NULL,
ma_obj2 = NULL,
ma_method = c("bb", "ic", "ad"),
correction_type = c("ts", "vgx", "vgy"),
conf_level = NULL
)
An object of class anova.ma_psychmeta
. A tibble with a row for each construct pair in object
and a column for each moderator tested. Cells lists of contrasts tested.
A psychmeta meta-analysis object.
Additional arguments.
Which analyses to to test moderators for? Can be either "all"
to test moderators for all meta-analyses in the object (default) or a list containing one or more of the arguments construct
, construct_pair
, pair_id
, k_min
, and N_min
. See filter_ma()
for details. Note that analysis_id
should not be used. If k_min
is not supplied, it is set to 2.
A character vector of moderators to test. If NULL
, all categorical moderators are tested.
A named list with with elements specifying set of linear contrasts for each variable in moderators
. (Not yet implemented.)
A second psychmeta meta-analysis object to compare to object
(Not yet implemented.)
Meta-analytic methods to be included. Valid options are: "bb", "ic", and "ad"
Types of meta-analytic corrections to be included. Valid options are: "ts", "vgx", and "vgy"
Confidence level to define the width of confidence intervals (defaults to value set when object
was fit)
ma_obj <- ma_r(rxyi, n, construct_x = x_name, construct_y = y_name,
moderators = moderator, data = data_r_meas_multi)
anova(ma_obj)
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