# Confounder-Adjusted Survival Curves and Cumulative Incidence Functions

## Documentation for package ‘adjustedCurves’ version 0.11.4

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

adjustedCurves-package | Confounder-Adjusted Survival Curves and Cumulative Incidence Functions
adjustedcif | Estimate Cause-Specific Confounder-Adjusted Cumulative Incidence Functions
adjustedsurv | Estimate Confounder-Adjusted Survival Curves
adjusted_curve_diff | Estimate the difference between or the ratio of two Confounder-Adjusted Survival Curves or CIFs
adjusted_curve_ratio | Estimate the difference between or the ratio of two Confounder-Adjusted Survival Curves or CIFs
adjusted_curve_test | Test if there is a difference between two Confounder-Adjusted Survival Curves or CIFs
adjusted_rmst | Estimate Confounder-Adjusted Restricted Mean Survival Times
adjusted_rmtl | Estimate Confounder-Adjusted Restricted Mean Time Lost
adjusted_surv_quantile | Estimate Confounder-Adjusted Survival Time Quantiles
as_ggsurvplot_df | Extract a 'data.frame' containing the estimated survival curves from a 'adjustedsurv' object
cif_aalen_johansen | Group-Specific Aalen-Johansen CIFs
cif_aiptw | Augmented Inverse Probability of Treatment Weighted CIFs
cif_aiptw_pseudo | Augmented Inverse Probability of Treatment Weighted CIFs using Pseudo-Values
cif_direct | Direct Adjusted Cumulative Incidence Functions
cif_direct_pseudo | Direct Adjusted CIFs using Pseudo-Values
cif_iptw | Inverse Probability of Treatment Weighted CIFs
cif_iptw_pseudo | Inverse Probability of Treatment Weighted CIFs using Pseudo-Values
cif_matching | Using Propensity-Score Matching to Calculate Adjusted CIFs
CSC_MI | Cause-Specific Cox Regression with Multiple Imputation
FGR_MI | Fine & Gray Model with Multiple Imputation
models_cif_direct | List of supported models in 'cif_direct'
models_surv_direct | List of supported models in 'surv_direct'
plot.adjustedcif | Plot Confounder-Adjusted Cumulative Incidence Functions
plot.adjustedsurv | Plot Confounder-Adjusted Survival Curves
plot.curve_test | Plot Method for 'curve_test' Objects
plot_curve_diff | Plot the Difference Between or the Ratio of Two Adjusted Survival Curves or CIFs
plot_curve_ratio | Plot the Difference Between or the Ratio of Two Adjusted Survival Curves or CIFs
plot_rmst_curve | Plot Adjusted Restricted Mean Survival Time Curves
plot_rmtl_curve | Plot Adjusted Restricted Mean Time Lost Curves
print.curve_test | Print Method for 'curve_test' Objects
sim_confounded_crisk | Simulate Competing Risks Data with Confounders
sim_confounded_surv | Simulate Survival Data with Confounders
surv_aiptw | Augmented Inverse Probability of Treatment Weighted Survival Curves
surv_aiptw_pseudo | Augmented Inverse Probability of Treatment Weighted Survival Curves using Pseudo-Values
surv_direct | Direct Adjusted Survival Curves
surv_direct_pseudo | Direct Adjusted Survival Curves using Pseudo-Values
surv_emp_lik | Empirical Likelihood Estimation Survival Curves
surv_iptw_cox | Inverse Probability of Treatment Weighted Survival using Cox-Regression
surv_iptw_km | Inverse Probability of Treatment Weighted Kaplan-Meier estimates
surv_iptw_pseudo | Inverse Probability of Treatment Weighted Survival Estimates using Pseudo-Values
surv_iv_2SRIF | Instrumental Variable based Survival Curve Estimation using the Two Stage Residual Inclusion method with a Frailty Term (2SRI-F)
surv_km | Group-Specific Kaplan-Meier Survival Curves
surv_matching | Using Propensity-Score Matching to Calculate Adjusted Survival Curves
surv_prox_aiptw | Proximal Augmented Inverse Probability of Treatment Weighted Survival Curve Estimates
surv_prox_iptw | Proximal Inverse Probability of Treatment Weighted Survival Curve Estimates
surv_strat_amato | Adjusted Survival Curves for Categorical Confounders using the Method by Amato (1988)
surv_strat_cupples | Adjusted Survival Curves for Categorical Confounders using the Method by Cupples et al. (1995)
surv_strat_nieto | Adjusted Survival Curves for Categorical Confounders using the Method by Gregory (1988) and Nieto & Coresh (1996)