Showing 3 of total 3 results (show query)
jucheng1992
ctmle:Collaborative Targeted Maximum Likelihood Estimation
Implements the general template for collaborative targeted maximum likelihood estimation. It also provides several commonly used C-TMLE instantiation, like the vanilla/scalable variable-selection C-TMLE (Ju et al. (2017) <doi:10.1177/0962280217729845>) and the glmnet-C-TMLE algorithm (Ju et al. (2017) <arXiv:1706.10029>).
Maintained by Cheng Ju. Last updated 5 years ago.
causal-inferencemachine-learningstatisticstmle
5 stars 4.83 score 27 scripts
jiayiji
CIMTx:Causal Inference for Multiple Treatments with a Binary Outcome
Different methods to conduct causal inference for multiple treatments with a binary outcome, including regression adjustment, vector matching, Bayesian additive regression trees, targeted maximum likelihood and inverse probability of treatment weighting using different generalized propensity score models such as multinomial logistic regression, generalized boosted models and super learner. For more details, see the paper by Hu et al. <doi:10.1177/0962280220921909>.
Maintained by Jiayi Ji. Last updated 3 years ago.
1.43 score 27 scripts
sg-tlr
twoStageDesignTMLE:Targeted Maximum Likelihood Estimation for Two-Stage Study Design
An inverse probability of censoring weighted (IPCW) targeted maximum likelihood estimator (TMLE) for evaluating a marginal point treatment effect from data where some variables were collected on only a subset of participants using a two-stage design (or marginal mean outcome for a single arm study). A TMLE for conditional parameters defined by a marginal structural model (MSM) is also available.
Maintained by Susan Gruber. Last updated 2 months ago.
1.30 score