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, ...)
```

error_type

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.

conf_level

Confidence level to define the width of the confidence interval (default = .95).

cred_level

Credibility level to define the width of the credibility interval (default = .80).

conf_method

Distribution to be used to compute the width of confidence intervals. Available options are "t" for *t* distribution or "norm" for normal distribution.

cred_method

Distribution to be used to compute the width of credibility intervals. Available options are "t" for *t* distribution or "norm" for normal distribution.

var_unbiased

Logical scalar determining whether variances should be unbiased (`TRUE`

) or maximum-likelihood (`FALSE`

).

pairwise_ads

Logical value that determines whether to compute artifact distributions in a construct-pair-wise fashion (`TRUE`

) or separately by construct (`FALSE`

, default).

moderated_ads

Logical value that determines whether to compute artifact distributions separately for each moderator combination (`TRUE`

) or for overall analyses only (`FALSE`

, default).

residual_ads

Logical argument that determines whether to use residualized variances (`TRUE`

) or observed variances (`FALSE`

) of artifact distributions to estimate `sd_rho`

.

check_dependence

Logical scalar that determines whether database should be checked for violations of independence (`TRUE`

) or not (`FALSE`

).

collapse_method

Character argument that determines how to collapse dependent studies. Options are "composite" (default), "average," and "stop."

intercor

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.

clean_artifacts

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.

impute_artifacts

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.

impute_method

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

Seed value to use for imputing artifacts in a reproducible way. Default value is 42.

use_all_arts

Logical scalar that determines whether artifact values from studies without valid effect sizes should be used in artifact distributions (`TRUE`

; default) or not (`FALSE`

).

estimate_pa

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).

decimals

Number of decimal places to which interactive artifact distributions should be rounded (default is 2 decimal places).

hs_override

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`

).

...

Further arguments to be passed to functions called within the meta-analysis.

A list of control arguments in the package environment.

# NOT RUN { control_psychmeta() # }

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