M-Estimation and Empirical Sandwich Variance Estimation
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Documentation for package ‘deli’ version 0.1.0
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A B C D E F G I L M N P R S T V W Z
-- A --
| actg175 | ACTG 175 clinical trial data |
| additive_design_matrix | Build an additive design matrix for GAMs |
| aft_predictions_function | Function-level predicted survival measures from an AFT model |
| aft_predictions_individual | Predicted survival measures from an AFT model |
| aggregate_efuncs | Aggregate estimating function contributions by group |
| augment.deli::deli_estimator | Augment data with predictions from a fitted deli estimator |
-- B --
| bonate_adverse | Bonate adverse events data |
| breast_cancer | Breast cancer survival data |
-- C --
| coef.deli::deli_estimator | Standard S3 generics for deli estimators |
| collett_bladder | Collett bladder cancer recurrence data |
| compute_confidence_bands | Compute confidence bands from theta and covariance |
| compute_sandwich | Compute the empirical sandwich variance estimator |
| confidence_bands | Confidence bands for parameter vectors |
| confidence_intervals | Confidence intervals for M-Estimator parameters |
| confint.deli::deli_estimator | Standard S3 generics for deli estimators |
| convert_survival_measures | Convert between survival analysis measures |
| crime | US state crime data |
| cutler1995 | Cutler (1995) pharmacodynamic data |
-- D --
| deli-augment | Augment data with predictions from a fitted deli estimator |
| deli-conditions | The condition classes deli raises |
| deli-display | Display methods for deli estimators |
| deli-generics | Standard S3 generics for deli estimators |
| deli-predict | Predictions from a fitted deli estimator |
| deli-tidiers | Broom tidiers for deli estimators |
| deli_digamma | Digamma function |
| deli_polygamma | Polygamma function |
| deli_spline | Generate polynomial spline basis terms |
| delta_method | Delta method for variance of transformed parameters |
| deviance.deli::deli_estimator | Standard S3 generics for deli estimators |
| df.residual.deli::deli_estimator | Standard S3 generics for deli estimators |
-- E --
| ee_2sls | Estimating equations for Two-Stage Least Squares (2SLS) |
| ee_additive_regression | Estimating equation for additive regression (GAM) |
| ee_aft | Estimating equation for accelerated failure time models |
| ee_aipw | Estimating equations for augmented inverse probability weighting (AIPW) |
| ee_beta_regression | Estimating equation for beta regression |
| ee_bridge_regression | Estimating equation for bridge penalized regression |
| ee_dlasso_regression | Estimating equation for differentiable LASSO regression |
| ee_elasticnet_regression | Estimating equation for elastic net regression |
| ee_emax | Estimating equation for E-max dose-response model |
| ee_emax_ed | Estimating equation for delta-effective dose (E-max) |
| ee_gestimation_snmm | Estimating equations for g-estimation of structural nested mean models |
| ee_gformula | Estimating equations for the g-formula (g-computation) |
| ee_glm | Estimating equation for generalized linear models |
| ee_ipw | Estimating equations for inverse probability weighting (IPW) |
| ee_ipw_msm | Estimating equations for IPW marginal structural model |
| ee_iv_causal | Estimating equations for instrumental variable (IV) estimation |
| ee_lasso_regression | Estimating equation for approximate LASSO regression |
| ee_loglogistic | Estimating equation for 4-parameter log-logistic dose-response model |
| ee_loglogistic_ed | Estimating equation for delta-effective dose (log-logistic) |
| ee_mean | Estimating equation for the mean |
| ee_mean_geometric | Estimating equation for the geometric mean |
| ee_mean_robust | Estimating equation for the robust mean |
| ee_mean_sensitivity_analysis | Estimating equations for weighted sensitivity analysis of the mean |
| ee_mean_variance | Estimating equations for the mean and variance |
| ee_mlogit | Estimating equation for multinomial logistic regression |
| ee_percentile | Estimating equation for the percentile |
| ee_plogit | Estimating equation for pooled logistic regression |
| ee_positive_mean_deviation | Estimating equations for the positive mean deviation |
| ee_regression | Estimating equation for regression |
| ee_regression_calibration | Estimating equation for regression calibration |
| ee_ridge_regression | Estimating equation for ridge regression |
| ee_robust_regression | Estimating equation for robust regression |
| ee_rogan_gladen | Estimating equation for Rogan-Gladen correction |
| ee_rogan_gladen_extended | Estimating equation for extended Rogan-Gladen correction |
| ee_survival_model | Estimating equation for parametric survival models |
| ee_tobit | Estimating equation for Tobit regression (Type I) |
| estimate | Estimate parameters and sandwich variance |
-- F --
| fitted.deli::deli_estimator | Standard S3 generics for deli estimators |
| formula.deli::deli_estimator | Standard S3 generics for deli estimators |
-- G --
| get_tested | GetTested randomized trial data |
| glance.deli::deli_estimator | Broom tidiers for deli estimators |
| GMMEstimator | GMM Estimator |
| gmm_estimate | One-step GMM estimation |
| gmm_estimate.default | One-step GMM estimation |
| gmm_estimate.formula | One-step GMM estimation |
-- I --
| identity_transform | Identity transformation |
| inderjit | Inderjit dose-response data |
| influence_functions | Influence functions for M-Estimator |
| inverse_logit | Inverse logistic transformation |
-- L --
| lau_wihs | Lau WIHS HIV/CD4 data |
| logit | Logistic transformation |
| logLik.deli::deli_estimator | Standard S3 generics for deli estimators |
-- M --
| MEstimator | M-Estimator |
| model.frame.deli::deli_estimator | Standard S3 generics for deli estimators |
| model.matrix.deli::deli_estimator | Standard S3 generics for deli estimators |
| mroz | Mroz labor force participation data |
| m_estimate | One-step M-estimation |
| m_estimate.default | One-step M-estimation |
| m_estimate.formula | One-step M-estimation |
-- N --
| nobs.deli::deli_estimator | Standard S3 generics for deli estimators |
| nsduh | NSDUH substance use survey data |
-- P --
| plogit_predict | Predicted survival measures from a pooled logistic regression model |
| pparg | PPARg cheminformatics data |
| predict.deli::deli_estimator | Predictions from a fitted deli estimator |
| print.deli::deli_estimator | Display methods for deli estimators |
| p_values | P-values for M-Estimator parameters |
-- R --
| regression_predictions | Generate predicted values from a regression model |
| residuals.deli::deli_estimator | Standard S3 generics for deli estimators |
| robust_loss_functions | Robust loss function derivatives |
| robust_regress | Robust regression example data |
-- S --
| sdss_quasar | SDSS quasar survey data |
| shaq_free_throws | Shaquille O'Neal free throw data |
| sigma.deli::deli_estimator | Standard S3 generics for deli estimators |
| standard_normal_cdf | Standard normal CDF |
| standard_normal_pdf | Standard normal PDF |
| summary.deli::deli_estimator | Display methods for deli estimators |
| survival_predictions | Generate predicted survival measures from a parametric survival model |
| s_values | S-values (surprisal) for M-Estimator parameters |
-- T --
| terms.deli::deli_estimator | Standard S3 generics for deli estimators |
| tidy.deli::deli_estimator | Broom tidiers for deli estimators |
-- V --
| vcov.deli::deli_estimator | Standard S3 generics for deli estimators |
-- W --
| weights.deli::deli_estimator | Standard S3 generics for deli estimators |
-- Z --
| z_scores | Z-scores for M-Estimator parameters |