est_med {vaccine} | R Documentation |
Estimate mediation effects
Description
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 |
Value
A dataframe containing the following columns:
effect
: one of c("NDE", "NIE", "PM")est
: point estimatese
: standard error of point estimateci_lower
: a confidence interval lower limitci_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)
ests_np <- est_med(dat=dat, type="NP", t_0=578)