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Estimate mediation effects

Source: R/est_med.R
est_med.Rd

Estimate mediation effects, including the natural direct effect (NDE), the natural indirect effect (NIE), and the proportion mediated (PM). See references for definitions of these objects.

Usage

est_med(
  dat,
  type = "NP",
  t_0,
  nde = TRUE,
  nie = TRUE,
  pm = TRUE,
  scale = "RR",
  params_np = params_med_np()
)

Arguments

dat

A data object returned by load_data

type

One of c("NP", "Cox"). This specifies whether to estimate the effects using a marginalized Cox proportional hazards model or using a nonparametric estimator.

t_0

Time point of interest

nde

Boolean. If TRUE, the natural direct effect is computed and returned.

nie

Boolean. If TRUE, the natural indirect effect is computed and returned.

pm

Boolean. If TRUE, the proportion mediated is computed and returned.

scale

One of c("RR", "VE"). This determines whether NDE and NIE estimates and CIs are computed on the risk ratio (RR) scale or the vaccine efficacy (VE) scale. The latter equals one minus the former.

params_np

A list of options returned by params_med_np that are relevant if type="NP".

Value

A dataframe containing the following columns:

  • effect: one of c("NDE", "NIE", "PM")

  • est: point estimate

  • se: standard error of point estimate

  • ci_lower: a confidence interval lower limit

  • ci_upper: a confidence interval upper limit

References

Fay MP and Follmann DA (2023). Mediation Analyses for the Effect of Antibodies in Vaccination <doi:10.48550/arXiv.2208.06465>

Examples

data(hvtn505)
dat <- load_data(time="HIVwk28preunblfu", event="HIVwk28preunbl", vacc="trt",
                 marker="IgG_V2", covariates=c("age","BMI","bhvrisk"),
                 weights="wt", ph2="casecontrol", data=hvtn505)
# \donttest{
ests_np <- est_med(dat=dat, type="NP", t_0=578)
# }