Package index

Study designs

Constructors for observational, experimental, and clustered-interference designs.

observational()

Create an Observational Study Object

experimental()

Create an Experimental Study Object

clustered()

Create a Clustered Interference Study Object

crd()

Completely Randomized Design

bernoulli()

Bernoulli Randomized Design

draw()

Draw Treatment Assignment

get_params_via_obs()

Infer Design Parameters from Observed Treatment

Estimators

Estimation methods for causal effects and randomization tests.

estimate()

Default Estimation

est_via_ols()

OLS Estimator

est_via_ipw()

IPW Estimator

est_via_aipw()

AIPW (Doubly Robust) Estimator

est_via_matching()

Matching Estimator

est_via_dml()

Double/Debiased Machine Learning Estimator

est_via_dm()

Difference-in-Means Estimator

est_via_strata()

Stratified Estimator

est_via_ancova()

ANCOVA Estimator

test_via_fisher()

Fisher Randomization Test

Data generation and models

generate_data()

Generate Observational Data

generate_data_continuous()

Generate Observational Data with Continuous Treatment

generate_clustered_data()

Generate Clustered Data with Varying Cluster Sizes

generate_fixed_cluster()

Generate Fixed-Size Cluster Data with Interference

po_data()

Create a Potential Outcome Data Container

get_balance()

Compute Rerandomization Balance Criterion

cm_ols()

OLS Model Wrapper

cm_logistic()

Logistic Regression Model Wrapper

cm_multi_logistic()

Multinomial Logistic Regression Model Wrapper

cm_random_forest_regressor()

Random Forest Regressor Wrapper

cm_random_forest_classifier()

Random Forest Classifier Wrapper

cm_result()

Create a Causal Model Result