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CIMTx  

Causal Inference for Multiple Treatments with a Binary Outcome
View on CRAN: Click here


Download and install CIMTx package within the R console
Install from CRAN:
install.packages("CIMTx")

Install from Github:
library("remotes")
install_github("cran/CIMTx")

Install by package version:
library("remotes")
install_version("CIMTx", "1.2.0")



Attach the package and use:
library("CIMTx")
Maintained by
Jiayi Ji
[Scholar Profile | Author Map]
First Published: 2020-04-15
Latest Update: 2022-06-24
Description:
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. .
How to cite:
Jiayi Ji (2020). CIMTx: Causal Inference for Multiple Treatments with a Binary Outcome. R package version 1.2.0, https://cran.r-project.org/web/packages/CIMTx. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2020-04-15 12:30), 0.2.0 (2020-06-02 18:40), 0.3.0 (2021-07-16 10:20), 1.0.0 (2021-10-20 09:10), 1.1.0 (2021-11-30 00:10)
Other packages that cited CIMTx R package
View CIMTx citation profile
Other R packages that CIMTx depends, imports, suggests or enhances
Complete documentation for CIMTx
Functions, R codes and Examples using the CIMTx R package
Some associated functions: ce_estimate . ce_estimate_bart_ate . ce_estimate_bart_att . ce_estimate_iptw_ate . ce_estimate_iptw_ate_boot . ce_estimate_iptw_att . ce_estimate_iptw_att_boot . ce_estimate_ra_ate . ce_estimate_ra_att . ce_estimate_rams_ate . ce_estimate_rams_ate_boot . ce_estimate_rams_att . ce_estimate_rams_att_boot . ce_estimate_tmle_ate . ce_estimate_tmle_ate_boot . ce_estimate_vm_att . covariate_overlap . data_sim . plot.CIMTx_ATE_posterior . plot.CIMTx_ATT_posterior . plot.CIMTx_IPTW . plot.CIMTx_nonIPTW_once . plot.CIMTx_sa_grid . posterior_summary . print.CIMTx_ATE_posterior . print.CIMTx_ATE_sa . print.CIMTx_ATT_posterior . print.CIMTx_ATT_sa . print.CIMTx_IPTW . print.CIMTx_nonIPTW_once . print.CIMTx_sa_grid . sa . summary.CIMTx_ATE_posterior . summary.CIMTx_ATE_sa . summary.CIMTx_ATT_posterior . summary.CIMTx_ATT_sa . summary.CIMTx_IPTW . summary.CIMTx_nonIPTW_once . true_c_fun_cal . trunc_fun . 
Some associated R codes: ce_estimate.R . ce_estimate_bart_ate.R . ce_estimate_bart_att.R . ce_estimate_iptw_ate.R . ce_estimate_iptw_ate_boot.R . ce_estimate_iptw_att.R . ce_estimate_iptw_att_boot.R . ce_estimate_ra_ate.R . ce_estimate_ra_att.R . ce_estimate_rams_ate.R . ce_estimate_rams_ate_boot.R . ce_estimate_rams_att.R . ce_estimate_rams_att_boot.R . ce_estimate_tmle_ate.R . ce_estimate_tmle_ate_boot.R . ce_estimate_vm_att.R . covariate_overlap.R . data_sim.R . plot.CIMTx_ATE_posterior.R . plot.CIMTx_ATT_posterior.R . plot.CIMTx_IPTW.R . plot.CIMTx_nonIPTW_once.R . plot.CIMTx_sa_grid.R . posterior_summary.R . print.CIMTx_ATE_posterior.R . print.CIMTx_ATE_sa.R . print.CIMTx_ATT_posterior.R . print.CIMTx_ATT_sa.R . print.CIMTx_IPTW.R . print.CIMTx_nonIPTW_once.R . print.CIMTx_sa_grid.R . sa.R . summary.CIMTx_ATE_posterior.R . summary.CIMTx_ATE_sa.R . summary.CIMTx_ATT_posterior.R . summary.CIMTx_ATT_sa.R . summary.CIMTx_IPTW.R . summary.CIMTx_nonIPTW_once.R . true_c_fun_cal.R . trunc_fun.R .  Full CIMTx package functions and examples
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