README.md

In denisagniel/synthate: Synthetic Causal Inference

synthate package: Synthetic estimators for the average treatment effect

This package comprises a suite of tools to simulate various data-generating processes. Its purpose is to check the operating characteristics of various causal estimators and to optimally combine them.

Installation

The synthate package can currently be obtained from GitLab: https://code.rand.org/agniel-projects/personal-packages/synthate or from GitHub at https://github.com/denisagniel/synthate. It may be downloaded by running

devtools::install_github('denisagniel/synthate')

Overview

There are three main features of synthate:

• Simulating data
• Causal estimation
• Combining estimators

Simulating data

There are currently seven DGPs derived from six different papers to choose from:

| Short-hand | Paper | |------------|--------------------------------------------------| | ks | Kang and Schafer (Kang and Schafer (2007)) | | ld | Lunceford and Davidian (Lunceford et al. (2004)) | | iw | Waernbaum (Waernbaum (2012)) | | fi | Fan and Imai (Fan (2016)) | | pa | Austin (Austin (2009)) | | ls | Leacy and Stuart (Leacy and Stuart (2014)) | | ik | Iacus and King (Iacus, King, and Porro (2009)) |

References

Austin, Peter C. 2009. “Some methods of propensity-score matching had superior performance to others: results of an empirical investigation and monte carlo simulations.” Biometrical Journal 51 (1): 171–84. doi:10.1002/bimj.200810488.

Fan, Jianqing. 2016. “Improving Covariate Balancing Propensity Score : A Doubly Robust and Efficient Approach ∗,” 1–47.

Iacus, Stefano M., Gary King, and Giuseppe Porro. 2009. “<b>cem</b> : Software for Coarsened Exact Matching.” Journal of Statistical Software 30 (9). doi:10.18637/jss.v030.i09.

Kang, Joseph D. Y., and Joseph L. Schafer. 2007. “Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data.” Statistical Science 22 (4): 523–39. doi:10.1214/07-STS227.

Leacy, Finbarr P., and Elizabeth A. Stuart. 2014. “On the joint use of propensity and prognostic scores in estimation of the ATT: A simulation study.” Statistics in Medicine 33 (20): 161–69. doi:10.3851/IMP2701.Changes.

Lunceford, Jared K, Jared K Lunceford, Marie Davidian, and Marie Davidian. 2004. “Stratification and weighting via the propensity score in estimation of causal treatment e ects: a comparative study.” Statistics in Medicine 2960 (19): 2937–60. doi:10.1002/sim.1903.

Waernbaum, Ingeborg. 2012. “Model misspecification and robustness in causal inference: Comparing matching with doubly robust estimation.” Statistics in Medicine 31 (15): 1572–81. doi:10.1002/sim.4496.

denisagniel/synthate documentation built on April 16, 2020, 12:45 a.m.