Fit the inverse-probability weight factor for an in-memory cohort and return the per-(id, period) factor table (id, period, weight_factor) as a data.frame — the frame-in/frame-out analogue of fit_weights_parquet().

Fit the inverse-probability weight factor for an in-memory cohort and return the per-(id, period) factor table (id, period, weight_factor) as a data.frame — the frame-in/frame-out analogue of fit_weights_parquet().

Usage

fit_weights_df(
  cohort,
  id_col,
  period_col,
  treatment_col,
  eligible_col,
  outcome_col,
  first_period,
  last_period,
  estimand,
  use_switch,
  switch_numerator,
  switch_denominator,
  use_censor,
  censor_col,
  censor_numerator,
  censor_denominator,
  pool_censor
)

Arguments

cohort

An R data.frame of long person-time rows.

id_col, period_col, treatment_col

Column names in cohort.

eligible_col, outcome_col

Eligibility / outcome column names.

first_period, last_period

Inclusive integer bounds on trial_period.

estimand

"ITT" or "PP". Case-insensitive.

use_switch

Whether to fit per-protocol switching-weight models.

switch_numerator, switch_denominator

Covariate columns for the switching numerator/denominator models (ignored when use_switch is FALSE).

use_censor

Whether to fit inverse-probability-of-censoring (IPCW) models.

censor_col

Name of the {0,1} censoring-indicator column; the response is 1 - censor_col (ignored when use_censor is FALSE).

censor_numerator, censor_denominator

Covariate columns for the IPCW numerator/denominator models (ignored when use_censor is FALSE).

pool_censor

How the IPCW models are pooled across the previous-treatment strata: "none", "numerator", or "both". Case-insensitive.

Value

A data.frame with columns id, period, weight_factor (a 64-bit integer id is returned as bit64::integer64). Errors in the core engine (including weight-fit failures) surface as R errors.