Control for psychmeta meta-analyses
control_psychmeta(
error_type = c("mean", "sample"),
conf_level = 0.95,
cred_level = 0.8,
conf_method = c("t", "norm"),
cred_method = c("t", "norm"),
var_unbiased = TRUE,
pairwise_ads = FALSE,
moderated_ads = FALSE,
residual_ads = TRUE,
check_dependence = TRUE,
collapse_method = c("composite", "average", "stop"),
intercor = control_intercor(),
clean_artifacts = TRUE,
impute_artifacts = TRUE,
impute_method = c("bootstrap_mod", "bootstrap_full", "simulate_mod", "simulate_full",
"wt_mean_mod", "wt_mean_full", "unwt_mean_mod", "unwt_mean_full", "replace_unity",
"stop"),
seed = 42,
use_all_arts = TRUE,
estimate_pa = FALSE,
decimals = 2,
hs_override = FALSE,
zero_substitute = .Machine$double.eps,
...
)A list of control arguments in the package environment.
Method to be used to estimate error variances: "mean" uses the mean effect size to estimate error variances and "sample" uses the sample-specific effect sizes.
Confidence level to define the width of the confidence interval (default = .95).
Credibility level to define the width of the credibility interval (default = .80).
Distribution to be used to compute the width of confidence intervals. Available options are "t" for t distribution or "norm" for normal distribution.
Distribution to be used to compute the width of credibility intervals. Available options are "t" for t distribution or "norm" for normal distribution.
Logical scalar determining whether variances should be unbiased (TRUE) or maximum-likelihood (FALSE).
Logical value that determines whether to compute artifact distributions in a construct-pair-wise fashion (TRUE) or separately by construct (FALSE, default).
Logical value that determines whether to compute artifact distributions separately for each moderator combination (TRUE) or for overall analyses only (FALSE, default).
Logical argument that determines whether to use residualized variances (TRUE) or observed variances (FALSE) of artifact distributions to estimate sd_rho.
Logical scalar that determines whether database should be checked for violations of independence (TRUE) or not (FALSE).
Character argument that determines how to collapse dependent studies. Options are "composite" (default), "average," and "stop."
The intercorrelation(s) among variables to be combined into a composite. Can be a scalar, a named vector with element named according to the names of constructs, or output from the control_intercor function. Default scalar value is .5.
If TRUE, multiple instances of the same construct (or construct-measure pair, if measure is provided) in the database are compared and reconciled with each other
in the case that any of the matching entries within a study have different artifact values. When impute_method is anything other than "stop", this method is always implemented to prevent discrepancies among imputed values.
If TRUE, artifact imputation will be performed (see impute_method for imputation procedures). Default is FALSE for artifact-distribution meta-analyses and TRUE otherwise.
When imputation is performed, clean_artifacts is treated as TRUE so as to resolve all discrepancies among artifact entries before and after imputation.
Method to use for imputing artifacts. Choices are:
"bootstrap_mod": Select random values from the most specific moderator categories available (default).
"bootstrap_full": Select random values from the full vector of artifacts.
"simulate_mod": Generate random values from the distribution with the mean and variance of observed artifacts from the most specific moderator categories available.
(uses rnorm for u ratios and rbeta for reliability values).
"simulate_full": Generate random values from the distribution with the mean and variance of all observed artifacts (uses rnorm for u ratios and rbeta for reliability values).
"wt_mean_mod": Replace missing values with the sample-size weighted mean of the distribution of artifacts from the most specific moderator categories available (not recommended).
"wt_mean_full": Replace missing values with the sample-size weighted mean of the full distribution of artifacts (not recommended).
"unwt_mean_mod": Replace missing values with the unweighted mean of the distribution of artifacts from the most specific moderator categories available (not recommended).
"unwt_mean_full": Replace missing values with the unweighted mean of the full distribution of artifacts (not recommended).
"replace_unity": Replace missing values with 1 (not recommended).
"stop": Stop evaluations when missing artifacts are encountered.
If an imputation method ending in "mod" is selected but no moderators are provided, the "mod" suffix will internally be replaced with "full".
Seed value to use for imputing artifacts in a reproducible way. Default value is 42.
Logical scalar that determines whether artifact values from studies without valid effect sizes should be used in artifact distributions (TRUE; default) or not (FALSE).
Logical scalar that determines whether the unrestricted subgroup proportions associated with univariate-range-restricted effect sizes should be estimated by rescaling the range-restricted subgroup proportions as a function of the range-restriction correction (TRUE) or not (FALSE; default).
Number of decimal places to which interactive artifact distributions should be rounded (default is 2 decimal places).
When TRUE, this will override settings for wt_type (will set to "sample_size"),
error_type (will set to "mean"),
correct_bias (will set to TRUE),
conf_method (will set to "norm"),
cred_method (will set to "norm"),
var_unbiased (will set to FALSE),
residual_ads (will be set to FALSE),
and use_all_arts (will set to FALSE).
Value to be used as a functionally equivalent substitute for exactly zero effect sizes in individual-correction meta-analyses to facilitate the estimation of corrected error variances. By default, this is set to .Machine$double.eps.
Further arguments to be passed to functions called within the meta-analysis.