Direct Effects from Estimated Model
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 indirect effect.
- t2
The alternative level of the treatment to be used when computing the indirect effect.
Value
A data.frame summarizing the overall indirect effects associated with different settings of j in the equation above.
Details
Estimate direct effects associated with a multimedia model. These estimates are formed using Equation (10) of our preprint.
Examples
# example with null data
exper <- demo_joy() |>
mediation_data("PHQ", "treatment", starts_with("ASV"))
fit <- multimedia(exper) |>
estimate(exper)
indirect_overall(fit)
#> outcome direct_setting contrast indirect_effect
#> 1 PHQ Control Control - Treatment -0.01115625
#> 2 PHQ Treatment Control - Treatment -0.01115625
# example with another dataset
exper <- demo_spline(tau = c(2, 1)) |>
mediation_data(starts_with("outcome"), "treatment", "mediator")
fit <- multimedia(exper) |>
estimate(exper)
indirect_overall(fit)
#> outcome direct_setting contrast indirect_effect
#> 1 outcome_1 0 0 - 1 0.5150703
#> 2 outcome_2 0 0 - 1 -0.7037543
#> 3 outcome_1 1 0 - 1 0.5150703
#> 4 outcome_2 1 0 - 1 -0.7037543