causatr
  1. Reference
  2. print.causatr_glmtp
  • Home
  • Getting started
    • Introduction
  • Estimation methods
    • G-computation with causatr
    • Inverse probability weighting with causatr
    • Augmented IPW (doubly-robust estimation) with causatr
    • Propensity score matching with causatr
    • Structural nested mean models with causatr
  • Interventions
    • Intervention types
    • Natural-history MTPs (grace periods)
  • Advanced topics
    • Methodological triangulation: g-computation, IPW, AIPW, matching, and SNM
    • Longitudinal treatments: ICE g-computation
    • Transportability and generalizability
    • Handling missing data
    • Diagnostics with causatr
    • Validation against reference implementations
  • Theory
    • Variance estimation
    • IPW variance theory
  • Reference
    • carry_forward
    • causat_mice
    • causat
    • coef.causatr_result
    • confint.causatr_result
    • contrast
    • diagnose
    • dynamic
    • glance.causatr_result
    • grace_period
    • ipsi
    • nhefs
    • plot.causatr_diag
    • plot.causatr_result
    • print.causatr_diag
    • print.causatr_fit
    • print.causatr_glmtp
    • print.causatr_intervention
    • print.causatr_result
    • scale_by
    • shift
    • static
    • stochastic
    • summary.causatr_diag
    • summary.causatr_fit
    • summary.causatr_result
    • target_trial
    • threshold
    • tidy.causatr_result
    • to_person_period
    • vcov.causatr_result
  • News
  • License
  • Citation

On this page

  • Print a natural-history (G-LMTP) intervention
    • Description
    • Usage
    • Arguments
    • Value

Code Links

  1. Reference
  2. print.causatr_glmtp

Print a natural-history (G-LMTP) intervention

Description

Displays the policy family and its scalar parameters; the policy closure is shown as a placeholder rather than deparsed.

Usage

## S3 method for class 'causatr_glmtp'
print(x, ...)

Arguments

x A causatr_glmtp object.
… Currently unused.

Value

Invisibly returns x.