Index _ | A | B | C | D | E | F | G | I | K | M | O | P | R | S | T | U | V | X _ __init__() (causalis.data.causaldata.CausalData method), [1], [2] (causalis.data.generators.CausalDatasetGenerator method) (causalis.eda.CausalDataLite method), [1] (causalis.eda.CausalEDA method), [1] (causalis.eda.eda.CausalDataLite method), [1] (causalis.eda.eda.CausalEDA method) (causalis.eda.eda.OutcomeModel method) (causalis.eda.eda.PropensityModel method) __repr__() (causalis.data.causaldata.CausalData method), [1] A add_score_flags() (in module causalis.refutation.score.score_validation), [1] aipw_score_ate() (in module causalis.refutation.score.score_validation), [1] aipw_score_atte() (in module causalis.refutation.score.score_validation), [1] alpha_d (causalis.data.generators.CausalDatasetGenerator attribute) alpha_y (causalis.data.generators.CausalDatasetGenerator attribute) auc_m() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method) B beta_d (causalis.data.generators.CausalDatasetGenerator attribute) beta_y (causalis.data.generators.CausalDatasetGenerator attribute) bootstrap_diff_means() (in module causalis.inference) C cate_esimand() (in module causalis.inference.cate.cate_esimand) CausalData (class in causalis.data.causaldata), [1] CausalDataLite (class in causalis.eda) (class in causalis.eda.eda), [1] CausalDatasetGenerator (class in causalis.data.generators) CausalEDA (class in causalis.eda) (class in causalis.eda.eda) causalis.data.generators module causalis.eda.eda module causalis.inference.ate.dml_ate module causalis.inference.atte.conversion_z_test module causalis.inference.atte.dml_atte module causalis.inference.atte.ttest module causalis.inference.cate.cate_esimand module causalis.inference.gate.gate_esimand module causalis.refutation.score.score_validation module, [1] causalis.refutation.unconfoundedness.uncofoundedness_validation module confounder_specs (causalis.data.generators.CausalDatasetGenerator attribute) confounders (causalis.data.causaldata.CausalData attribute), [1] (causalis.data.causaldata.CausalData property), [1] (causalis.eda.CausalDataLite attribute) (causalis.eda.eda.CausalDataLite attribute), [1] confounders_means() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] confounders_roc_auc() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] conversion_z_test() (in module causalis.inference) (in module causalis.inference.atte.conversion_z_test) copula_corr (causalis.data.generators.CausalDatasetGenerator attribute) D data_shape() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] df (causalis.data.causaldata.CausalData attribute), [1] (causalis.eda.CausalDataLite attribute) (causalis.eda.eda.CausalDataLite attribute), [1] dml_ate() (in module causalis.inference.ate.dml_ate) dml_atte() (in module causalis.inference.atte.dml_atte) dml_atte_source() (in module causalis.inference) E extract_nuisances() (in module causalis.refutation.score.score_validation), [1] F fit_m() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method) fit_propensity() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] from_kfold() (causalis.eda.eda.OutcomeModel class method) (causalis.eda.eda.PropensityModel class method) G g_d (causalis.data.generators.CausalDatasetGenerator attribute) g_y (causalis.data.generators.CausalDatasetGenerator attribute) gate_esimand() (in module causalis.inference.gate.gate_esimand) generate() (causalis.data.generators.CausalDatasetGenerator method) generate_rct() (in module causalis.data.generators) generate_rct_data() (in module causalis.data.generators), [1] get_df() (causalis.data.causaldata.CausalData method), [1] get_sensitivity_summary() (in module causalis.refutation) I influence_summary() (in module causalis.refutation.score.score_validation), [1] K k (causalis.data.generators.CausalDatasetGenerator attribute) M m_features() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method) module causalis.data.generators causalis.eda.eda causalis.inference.ate.dml_ate causalis.inference.atte.conversion_z_test causalis.inference.atte.dml_atte causalis.inference.atte.ttest causalis.inference.cate.cate_esimand causalis.inference.gate.gate_esimand causalis.refutation.score.score_validation, [1] causalis.refutation.unconfoundedness.uncofoundedness_validation O oos_moment_check() (in module causalis.refutation.score.score_validation), [1] oos_moment_check_from_psi() (in module causalis.refutation.score.score_validation), [1] oos_moment_check_with_fold_nuisances() (in module causalis.refutation.score.score_validation), [1] Optional (causalis.eda.CausalEDA attribute) (causalis.eda.eda.CausalEDA attribute) oracle_nuisance() (causalis.data.generators.CausalDatasetGenerator method) orthogonality_derivatives() (in module causalis.refutation.score.score_validation), [1] orthogonality_derivatives_atte() (in module causalis.refutation.score.score_validation), [1] outcome (causalis.data.causaldata.CausalData attribute), [1] (causalis.data.causaldata.CausalData property), [1] outcome_boxplot() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method) outcome_fit() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] outcome_hist() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method) outcome_plots() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] outcome_stats() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] outcome_type (causalis.data.generators.CausalDatasetGenerator attribute) OutcomeModel (class in causalis.eda.eda) overlap_diagnostics_atte() (in module causalis.refutation.score.score_validation), [1] P plot_m_overlap() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method) (causalis.eda.eda.PropensityModel method) plot_ps_overlap() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] positivity_check() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] (causalis.eda.eda.PropensityModel method) positivity_check_m() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method) (causalis.eda.eda.PropensityModel method) propensity_scores (causalis.eda.eda.PropensityModel property) propensity_sharpness (causalis.data.generators.CausalDatasetGenerator attribute) PropensityModel (class in causalis.eda.eda) ps_graph() (causalis.eda.eda.PropensityModel method) R refute_irm_orthogonality() (in module causalis.refutation) (in module causalis.refutation.score.score_validation), [1] refute_placebo_outcome() (in module causalis.refutation) (in module causalis.refutation.score.score_validation), [1] refute_placebo_treatment() (in module causalis.refutation) (in module causalis.refutation.score.score_validation), [1] refute_subset() (in module causalis.refutation) (in module causalis.refutation.score.score_validation), [1] rng (causalis.data.generators.CausalDatasetGenerator attribute), [1] roc_auc (causalis.eda.eda.PropensityModel property) run_score_diagnostics() (in module causalis.refutation.score.score_validation), [1] run_unconfoundedness_diagnostics() (in module causalis.refutation.unconfoundedness.uncofoundedness_validation) S scores (causalis.eda.eda.OutcomeModel property) seed (causalis.data.generators.CausalDatasetGenerator attribute) sensitivity_analysis() (in module causalis.refutation) shap (causalis.eda.eda.OutcomeModel property) (causalis.eda.eda.PropensityModel property) sigma_y (causalis.data.generators.CausalDatasetGenerator attribute) T target (causalis.data.causaldata.CausalData property), [1] (causalis.eda.CausalDataLite attribute) (causalis.eda.eda.CausalDataLite attribute), [1] target_d_rate (causalis.data.generators.CausalDatasetGenerator attribute) tau (causalis.data.generators.CausalDatasetGenerator attribute) theta (causalis.data.generators.CausalDatasetGenerator attribute) to_causal_data() (causalis.data.generators.CausalDatasetGenerator method) treatment (causalis.data.causaldata.CausalData attribute), [1] (causalis.data.causaldata.CausalData property), [1] (causalis.eda.CausalDataLite attribute) (causalis.eda.eda.CausalDataLite attribute), [1] treatment_features() (causalis.eda.CausalEDA method) (causalis.eda.eda.CausalEDA method), [1] trim_sensitivity_curve_ate() (in module causalis.refutation.score.score_validation), [1] trim_sensitivity_curve_atte() (in module causalis.refutation.score.score_validation), [1] ttest() (in module causalis.inference) (in module causalis.inference.atte.ttest) Tuple (causalis.eda.CausalEDA attribute) (causalis.eda.eda.CausalEDA attribute) U u_strength_d (causalis.data.generators.CausalDatasetGenerator attribute) u_strength_y (causalis.data.generators.CausalDatasetGenerator attribute) use_copula (causalis.data.generators.CausalDatasetGenerator attribute) V validate_unconfoundedness_balance() (in module causalis.refutation.unconfoundedness.uncofoundedness_validation) X x_sampler (causalis.data.generators.CausalDatasetGenerator attribute)
