direct_effect: Direct Effects from Estimated Model

In multimedia: Multimodal Mediation Analysis

Direct Effects from Estimated Model

Description

Estimate direct effects associated with a multimedia model. These estimates are formed using Equation (10) of our paper. Rather than providing this average, this function returns the estimated difference for each $j$. To average across all j, this result can be passed to the ' effect_summary function.

Usage

direct_effect(model, exper = NULL, t1 = 1, t2 = 2)

Arguments

model	An object of class multimedia containing the estimated mediation and outcome models whose mediation and outcome predictions we want to compare.
exper	An object of class multimedia_data containing the mediation and outcome data from which the direct effects are to be estimated.
t1	The reference level of the treatment to be used when computing the direct effect.
t2	The alternative level of the treatment to be used when computing the direct effect.

Value

A data.frame summarizing the direct effects associated with different settings of j in the equation above.

See Also

effect_summary

Examples

# example with null data
exper <- demo_joy() |>
    mediation_data("PHQ", "treatment", starts_with("ASV"))
fit <- multimedia(exper) |>
    estimate(exper)

direct_effect(fit)
direct_effect(fit, t1 = 2, t2 = 1)
direct_effect(fit, t1 = 2, t2 = 2)

# example with another dataset
exper <- demo_spline(tau = c(2, 1)) |>
    mediation_data(starts_with("outcome"), "treatment", "mediator")
fit <- multimedia(exper) |>
    estimate(exper)
direct_effect(fit)

multimedia documentation built on Sept. 30, 2024, 9:28 a.m.