Skip to contents

DGM Method

Source: R/dgm.R
dgm.Rd

S3 Method for defining data-generating mechanisms. See simulate_dgm() for usage and further details.

Usage

dgm(dgm_name, settings)

Arguments

dgm_name

Character string specifying the DGM type

settings

List containing the required parameters for the DGM or numeric condition_id

Output Structure

The returned data frame follows a standardized schema that downstream functions rely on. Across the currently implemented DGMs, the following columns are used:

  • yi (numeric): The effect size estimate.

  • sei (numeric): Standard error of yi.

  • ni (integer): Total sample size for the estimate (e.g., sum over groups where applicable).

  • es_type (character): Effect size type, used to disambiguate the scale of yi. Currently used values are "SMD" (standardized mean difference / Cohen's d), "logOR" (log odds ratio), and "none" (unspecified generic continuous coefficient).

  • study_id (integer/character, optional): Identifier of the primary study/cluster when a DGM yields multiple estimates per study (e.g., Alinaghi2018, PRE). If absent, each row is treated as an independent study.

See also

simulate_dgm()

Examples


simulate_dgm("Carter2019", 1)
#>             yi        sei   ni es_type
#> 1  -0.10800241 0.28888551   48     SMD
#> 2  -0.06930436 0.39235000   26     SMD
#> 3   0.49314901 0.38366643   28     SMD
#> 4   0.04244850 0.05976816 1120     SMD
#> 5   0.39060875 0.47587858   18     SMD
#> 6  -0.18115375 0.50102447   16     SMD
#> 7  -0.03658874 0.23572198   72     SMD
#> 8   0.25387417 0.23342995   74     SMD
#> 9   0.19210061 0.26321786   58     SMD
#> 10  0.88012881 0.60465647   12     SMD