Dynamic Path Analysis

Usage

dpa(
  out.formula,
  mediator.formulas,
  id,
  data,
  boot.n = 200,
  method = "timereg",
  progress_bar = FALSE,
  ...
)

Arguments

out.formula: Survival formula for Aalen's additive hazards model.
mediator.formulas: Mediator regression formula (in case of a single mediator), or a list of regression formulas (in case of multiple mediators). The formulas must be ordered according to Directed Acyclic Graph Structure (see Details).
id: character string indicating which column of 'data' corresponds to the subject ID. Bootstrapping will be performed on this id.
data: Data set in counting process format. In particular the data should contain a "start", "stop" and "event" column along with any mediators and baseline covariates.
boot.n: Number of bootstrap samples.
method: The underlying implementation of Aalen's additive regression model. Defaults to "timereg", which relies on the timereg::aalen() implementation, while method = "aareg" uses the survival::aareg() implementation.
progress_bar: Boolean. If TRUE, show progress bar. Defaults to FALSE.
...: other parameters passed to the Aalen's additive hazards model implementation. If method = "timereg", then ... will be passed to timereg::aalen(), while if method = "aareg", then ... will be passed to survival::aareg(). If ... contains parameters that don't belong to the formalArgs of the corresponding implementation then those parameters will be ignored.

Value

Object of class `dpa` with following fields:

coefs: list of estimated coefficients from each of the regressions listed in out.formula and mediator.formulas.
boot.coefs: list of bootstrap estimates corresponding to coefs. This stores all the bootstrap estimates to facilitate calculation of direct, indirect and total effects along with bootstrap confidence intervals.
meta: a list keeping track of responses and covariates of each of the out.formula and mediator.formulas. Also keeps track of all variable types and level names in case of factors.
aalen: Object storing information pertaining to the Aalen's additive model fit. Object is of class "aalen" if method="timereg", and of class "aareg" if method="aareg".

Details

dpa performs Dynamic Path Analysis of a Directed Acyclic Graph (DAG). The out.formula can have as covariates all mediators listed in mediator.formulas. The mediator.formulas must obey the following DAG structure rule: The response of the k-th formula cannot appear as covariate in any of the formulas k+1, ..., length(mediator.formulas).

Examples

library(dpasurv)

data(simdata)

set.seed(1)

# Perform dynamic path analysis:
# We set boot.n=30 for the example to run fast, should be set large enough
# so that results don't change meaningfully for different seeds.
s <- dpa(Surv(start,stop,event)~M+x, list(M~x), id="subject", data=simdata, boot.n=30)

# Calculate cumulative direct, indirect, and total effects:
direct <- effect(x ~ outcome, s)
indirect <- effect(x ~ M ~ outcome, s)
total <- sum(direct, indirect)

# Plot the effects using basic graphics:
layout1x3 <- par(mfrow=c(1,3))
plot(direct); abline(h=0, lty=2, col=2)
plot(indirect); abline(h=0, lty=2, col=2)
plot(total); abline(h=0, lty=2, col=2)


# restore user's graphical parameters:
par(layout1x3)

# Plot the effects using ggplot2 graphics:
ggplot.effect(list(direct, indirect, total))