estimate_psYpred: Estimator psYpred

In trangnguyen74/tnMediation: Simple and more robust estimation of marginal natural (in)direct effects

Estimator psYpred

Description

Function that implements estimator psYpred

Usage

estimate_psYpred(
  data,
  s.wt.var = NULL,
  cross.world = "10",
  effect.scale = "additive",
  a.c.form,
  max.stabilized.wt = 30,
  plot = TRUE,
  c.std = NULL,
  c.order = NULL,
  y.c1.form = NULL,
  y.c0.form = NULL,
  y.c.form = NULL,
  y.cm1.form = NULL,
  y.cm0.form = NULL,
  y.cm.form = NULL,
  y.link = "gaussian",
  boot.num = 999,
  boot.seed = NULL,
  boot.method = "cont-wt",
  boot.stratify = TRUE
)

Arguments

data	A data frame.
s.wt.var	Optional, name of variable containing sampling weights.
cross.world	The cross-world condition involved in the effect decomposition of choice. Should be "10" if want the (NDE0, NIE1) pair, "01" if want the (NIE0, NDE1) pair, or "both" if want both decompositions.
effect.scale	The scale of effect of choice. Defaults to "MD" (i.e., mean/risk difference or additive). If outcome is non-negative, also allows "mean ratio" (which could also be specified as "ratio", "MR", "risk ratio", "rate ratio", "RR"). If outcome is binary or bounded within the (0,1) interval, also allows "odds ratio" (which could also be specified as "OR").
a.c.form	Formula for the P(A|C) model (the propensity score model).
max.stabilized.wt	Max stabilized weight allowed. Larger weights are truncated to this level. Default is 30.
plot	Whether to output weight distribution and balance plots. Defaults to TRUE.
c.std	Covariates whose mean differences are to be standardized in balance plot. Ignore if plot==FALSE.
c.order	Order in which covariates are to be plotted. If not specify, use the order that appears in a.c.form.
y.c.form, y.c1.form, y.c0.form	blah
y.cm.form, y.cm1.form, y.cm0.form	blah
y.link	blah
boot.num	Number of bootstrap samples used for interval estimation, defaults to 999. If just want point estimate, set to 0.
boot.seed	Optional, specify bootstrap seed for reproducibility.
boot.method	Method for drawing bootstrap samples. Options: "cont-wt" for continuous weights bootstrap, and "resample" for bootstrap by simple resampling (i.e., integer weights bootstrap).
boot.stratify	Whether bootstrap samples are drawn stratified by treatment variable. Defaults to TRUE.

See Also

Other estimators: estimate_NDEpredR(), estimate_NDEpred(), estimate_Y2predR(), estimate_Y2pred(), estimate_YpredMR(), estimate_Ypred(), estimate_psYpredMR(), estimate_wpCadj(), estimate_wpMRCadj(), estimate_wtCadj(), estimate_wtd()

trangnguyen74/tnMediation documentation built on May 3, 2023, 6:58 a.m.