calc_iptw: Calculate total effect, natural direct and indirect effect.
In adayim/causalMed: Causal Mediation Analysis in Survival settings

Calculate total effect, natural direct and indirect effect.

calc_iptw(
  data,
  id.vars,
  time.var,
  baseline.vars,
  exposure.model,
  exposure.vars,
  mediator.model,
  mediator.family,
  outcome,
  is.expL = TRUE,
  censor.model = NULL,
  bound.value = 0
)

`data`	Data to be used to ceate matrix.
`id.vars`	ID variable name.
`time.var`	Time indexing varaible name.
`baseline.vars`	A vector of baseline variables and time-fixed variable names.
`exposure.model`	Exposure model, only binomial outcome supported.
`exposure.vars`	A vector of exposure variables, including lagged exposure variables.
`mediator.model`	Mediator model.
`mediator.family`	Model link function, `gussian`,`binomial` and `multinomial`. For multinomial model, `multinom` will be sued for model fitting. And `glm` for `gussian` and `binomial` link funciton model.
`outcome`	Outcome variable name.
`is.expL`	Is time-time varying exposure, defualt is TRUE.
`censor.model`	Censor model. Censoring indicator should be coded as remaing uncensored (as 1).
`bound.value`	Bound weights, between 0 and 0.5.