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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.

copied from cf-post-staging / r-lmtp
Type Size Name Uploaded Downloads Labels
conda 882.7 kB | noarch/r-lmtp-1.5.3-r45hc72bb7e_1.conda  6 months and 24 days ago 408 main
conda 882.6 kB | noarch/r-lmtp-1.5.3-r44hc72bb7e_1.conda  6 months and 24 days ago 419 main
conda 876.8 kB | noarch/r-lmtp-1.5.3-r43hc72bb7e_0.conda  8 months and 19 days ago 450 main
conda 882.4 kB | noarch/r-lmtp-1.5.3-r44hc72bb7e_0.conda  8 months and 19 days ago 454 main

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