Package: lmtp 1.4.0

Nicholas Williams

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

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.

Authors:Nicholas Williams [aut, cre, cph], Iván Díaz [aut, cph]

lmtp_1.4.0.tar.gz
lmtp_1.4.0.tar.gz(r-4.5-noble)lmtp_1.4.0.tar.gz(r-4.4-noble)
lmtp_1.4.0.tgz(r-4.4-emscripten)lmtp_1.4.0.tgz(r-4.3-emscripten)
lmtp.pdf |lmtp.html
lmtp/json (API)
NEWS

# Installlmtp in R:
install.packages('lmtp',repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/nt-williams/lmtp/issues

Datasets:

12 exports 0.36 score 30 dependencies 459 downloads

Last updated 8 days agofrom:501e7e3f62

Exports:create_node_listevent_locfipsilmtp_contrastlmtp_controllmtp_ipwlmtp_sdrlmtp_sublmtp_tmlestatic_binary_offstatic_binary_ontidy

Dependencies:abindassertthatbackportsbitopscaToolscheckmateclicodetoolscvAUCdata.tabledigestforeachfuturefuture.applygamgenericsglobalsgplotsgtoolsiteratorsKernSmoothlistenvnnlsorigamiparallellyprogressrR6ROCRschoolmathSuperLearner