Landmark Prediction of a Survival Outcome
Estimates the area under the ROC curve (AUC).
Estimates the Brier score.
Extract Coefficients from Landpred Continuous Model
Calculate Standard Errors for Coefficients
Helper function
Fit GLM with Normal Weights (No Short-term Event Info)
Fit GLM with Kernel Weights (Short-Term Event Info)
Get Landpred Model
Estimate Survival Function
Helper function for AUC.landmark
Calculates kernel matrix
Create a Landpred Object
Calculate MSE for Bandwidth Selection using Cross-Validation
Optimize Bandwidth for Continuous Landpred Models
Predict Method for Landpred Continuous Model
Predict Method for Discrete Landpred Model
Print Method for Landpred Continuous Model
Print Method for Discrete Landpred Model
Print Method for Landpred Object
Calculate Probability with Covariate Information
Calculate Probability with Short Event Information
Calculate Probability with No Information
Summary Method for Landpred Continuous Model
Summary Method for Landpred Object
Helper function, repeats a row.
Computes the inverse probability of censoring weights for a specific t...
Nonparametric methods for landmark prediction of long-term survival outcomes, incorporating covariate and short-term event information. The package supports the construction of flexible varying-coefficient models that use discrete covariates, as well as multiple continuous covariates. The goal is to improve prediction accuracy when censored short-term events are available as predictors, using robust nonparametric procedures that do not require correct model specification and avoid restrictive parametric assumptions found in alternative methods. More information on these methods can be found in Parast et al. 2012 <doi:10.1080/01621459.2012.721281>, Parast et al. 2011 <doi:10.1002/bimj.201000150>, and Parast and Cai 2013 <doi:10.1002/sim.5776>. A tutorial for this package is available here: <https://www.laylaparast.com/landpred>.