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Causalmodels: An R Library For Estimating Causal Effects, Joshua Wolff Anderson
Causalmodels: An R Library For Estimating Causal Effects, Joshua Wolff Anderson
Computational and Data Sciences (MS) Theses
Free and open source software for statistical modeling and machine learning have advanced productivity in data science significantly. Packages such as SciPy in Python and caret in R provide fundamental tools for statistical modeling and machine learning in the two most popular programming languages used by data scientists. Unfortunately, robust tools similar to these are limited in terms of causal inference. The tools in R that exist lack consistent and standardized methodologies and inputs. R lacks a comprehensive package that offers traditional causal inference methods such as standardization, IP weighting, G-estimation, outcome regression, and propensity matching in one common package. …