multimedia
objects encapsulate the model and data that underlie a mediation
analysis, together with metadata (like graph structure) that contextualize
the estimation. This function can be used to construct a new multimedia
instances from a mediation_data
dataset and pair of estimators.
Arguments
- mediation_data
An object of class
mediation_data
, with separate slots for each of the node types in a mediation analysis diagram.- outcome_estimator
An object of class
model
that will be used to estimate the outcome model.- mediation_estimator
An object of class
model
that will be used to estimate the mediation model.
Examples
exper <- demo_joy() |>
mediation_data("PHQ", "treatment", starts_with("ASV"))
multimedia(exper)
#> [Multimedia Analysis]
#> Treatments: treatment
#> Outcomes: PHQ
#> Mediators: ASV1, ASV2, ...
#>
#> [Models]
#> mediation: An unfitted lm_model().
#> outcome: An unfitted lm_model().
exper <- demo_spline(tau = c(2, 1)) |>
mediation_data(starts_with("outcome"), "treatment", "mediator")
multimedia(exper)
#> [Multimedia Analysis]
#> Treatments: treatment
#> Outcomes: outcome_1, outcome_2
#> Mediators: mediator
#>
#> [Models]
#> mediation: An unfitted lm_model().
#> outcome: An unfitted lm_model().
# real data example with a pretreatment variable
data(mindfulness)
exper <- mediation_data(
mindfulness,
phyloseq::taxa_names(mindfulness),
"treatment",
starts_with("mediator"),
"subject"
)
multimedia(exper)
#> [Multimedia Analysis]
#> Treatments: treatment
#> Outcomes: Acetanaerobacterium, Acidaminococcus, ...
#> Mediators: mediator.Cold.cereal, mediator.Fruit..not.juices., ...
#> Pretreatment: subject
#>
#> [Models]
#> mediation: An unfitted lm_model().
#> outcome: An unfitted lm_model().