View source: R/control_psychmeta.R

control_psychmeta | R Documentation |

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, ... )

`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 |

`cred_method` |
Distribution to be used to compute the width of credibility intervals. Available options are "t" for |

`var_unbiased` |
Logical scalar determining whether variances should be unbiased ( |

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

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

`residual_ads` |
Logical argument that determines whether to use residualized variances ( |

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

`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 |

`clean_artifacts` |
If |

`impute_artifacts` |
If |

`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 ( |

`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 ( |

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

`hs_override` |
When |

`zero_substitute` |
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 |

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

A list of control arguments in the package environment.

control_psychmeta()

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.