lmtp1.4.0 package

Non-Parametric Causal Effects of Feasible Interventions Based on Modified Treatment Policies

lmtp_sdr

LMTP Sequential Doubly Robust Estimator

lmtp_sub

LMTP Substitution Estimator

lmtp_tmle

LMTP Targeted Maximum Likelihood Estimator

create_node_list

Create a node list specification

event_locf

Time To Event Last Outcome Carried Forward

ipsi

IPSI Function Factory

lmtp_contrast

Perform Contrasts of LMTP Fits

lmtp_control

Set LMTP Estimation Parameters

lmtp_ipw

LMTP IPW Estimator

lmtp-package

lmtp: Non-Parametric Causal Effects of Feasible Interventions Based on...

reexports

Objects exported from other packages

static_binary_off

Turn All Treatment Nodes Off

static_binary_on

Turn All Treatment Nodes On

tidy.lmtp

Tidy a(n) lmtp object

Download source packageRead PDF manual

Non-parametric estimators for casual effects based on longitudinal modified treatment policies as described in Diaz, Williams, Hoffman, and Schenck <doi:10.1080/01621459.2021.1955691>, traditional point treatment, and traditional longitudinal effects. Continuous, binary, categorical treatments, and multivariate treatments are allowed as well are censored outcomes. The treatment mechanism is estimated via a density ratio classification procedure irrespective of treatment variable type. For both continuous and binary outcomes, additive treatment effects can be calculated and relative risks and odds ratios may be calculated for binary outcomes.

  • Maintainer: Nicholas Williams
  • License: AGPL-3
  • Last published: 2024-06-27

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