ice_pipeline: Iterated conditional DID g-formula estimator

In audreyrenson/didgformula: The difference-in-differences g-formula

Iterated conditional DID g-formula estimator

Description

Iterated conditional DID g-formula estimator

Usage

ice_pipeline(
  data,
  inside_formula_t,
  inside_formula_tmin1,
  outside_formula,
  Tt,
  inside_family = "gaussian",
  pt_link_fun = NULL,
  binomial_n = NULL,
  tibble = TRUE,
  models = TRUE,
  tmle = FALSE,
  weights = NULL
)

Arguments

data	Wide format data frame with one row per individual, and columns Yt for t = 0,1,...,Tt.
inside_formula_t	chr, right-hand-side formula for inside model for Yt
inside_formula_tmin1	chr, right-hand-side formula for inside model for Yt-1
outside_formula	chr, right-hand-side formula for outside models
Tt	int. max periods
inside_family	stats::family object or string referring to one, as in glm.
pt_link_fun	function. The scale on which parallel trends is assumed (e.g., qlogis for logit scale). Default NULL for untransformed scale.
binomial_n	int length nrow(data). Group sizes for binomial aggregate data.
tibble	logical. return results as a tibble (TRUE) or vector (FALSE)?
models	logical. Return all models as an attribute?
tmle	lgl. Incorporate tmle updating step to make estimator doubly robust?
weights	Matrix of IPTW weights as returned by cbind(1, calc_weights(...)). Default NULL, required if tmle=TRUE.

audreyrenson/didgformula documentation built on Oct. 9, 2022, 11:45 a.m.