iptw_pipeline: Estimate the DID g-formula using...

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

Estimate the DID g-formula using inverse-probability-of-treatment-weights.

Description

Estimate the DID g-formula using inverse-probability-of-treatment-weights.

Usage

iptw_pipeline(
  data,
  Tt,
  den_formula,
  num_formula = NULL,
  tibble = TRUE,
  pt_link_fun = NULL,
  binomial_n = 1,
  models = TRUE
)

Arguments

data	Wide format data frame with one row per individual, and columns Lt, At, Yt for t = 0,1,...,Tt.
Tt	int. Final period in dataset (t=0,1,...,Tt)
den_formula	chr. Right-hand-side glue-style formula to use in fitting treatment models for denominator. Format: '~L{t}+L{t-1}' etc.
num_formula	chr. Right-hand-side glue-style formula to use in fitting treatment models for numerator Format: '~L{t}+L{t-1}' etc.
tibble	logical. Should the results be returned as a tibble with columns (t, estimates) (TRUE) or a vector of just the estimates (FALSE)?
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 aggregate binomial data.
models	logical. Return all models as an attribute?

Value

Estimates of E(Yt(a) - Yt-1(a)), in the form of a tibble or vector (dependening on argument tibble), for times t=1,2,...,Tt (in that order).

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