Estimate covariate means for population represented in nomatch() estimand

Estimate covariate means for the weighted principal strata population represented in nomatch() estimand. Since the principal strata populations are not directly observed, simple summary statistics cannot be used. Instead, the means are estimated as weighted means where the weights depend on the both the original estimand weights and on predicted probabilities of belonging to different principal strata. Currently only implemented for the case when the estimand weights represent the observed distribution of exposure days and covariates among the exposed.

Usage

summarize_nomatch_population(data, fit)

Arguments

data: A data frame. The same data passed to nomatch().
fit: A nomatchfit object created by nomatch(). Must have been fit with keep_models = TRUE (the default) and weights_source = "observed".

Value

A data frame of the summary statistics with columns:

variable: Covariate name
label: Factor level label (empty string for numeric variables)
mean: Mean (or weighted proportion for factor levels)

Examples

fit <- nomatch(
  data = simdata,
  outcome_time = "Y",
  outcome_status = "event",
  exposure = "V",
  exposure_time = "D_obs",
  covariates = c("x1", "x2"),
  timepoints = seq(30, 180, by = 30),
  immune_lag = 14
)
summarize_nomatch_population(simdata, fit)
#>   variable label      mean
#> 1       x1       0.5035969
#> 2       x2       8.0659550