CIMTx: An R Package for Causal Inference with Multiple Treatments using Observational Data

Keyphrases

• Observational Data 100%
• Multiple Treatments 100%
• Causal Inference 100%
• Inverse Probability of Treatment Weighting 66%
• Regression Adjustment 66%
• Bayesian Additive Regression Trees 66%
• Vector Matching 66%
• Treatment Setting 33%
• Binary Outcome 33%
• Regression Vectors 33%
• Targeted Maximum Likelihood Estimation 33%
• Modern Methods 33%
• Tree Regression 33%
• Multivariate Splines 33%
• Generalized Propensity Score 33%
• Common Support 33%
• Support Region 33%
• Complex Data Structures 33%
• Causal Assumptions 33%
• Score Vector 33%
• Positivity Assumption 33%
• Tree Matching 33%
• Ignorability 33%

Mathematics

• Probability Theory 100%
• Bayesian 100%
• Causal Inference 100%
• Observational Data 100%
• Regression tree 100%
• Data Structure 50%
• Spline 50%
• Ignorability 50%
• Common Support 50%
• Unique Set 50%
• Maximum Likelihood 50%