• Corpus ID: 252734945

Regression discontinuity design with right-censored survival data

@inproceedings{Stoltenberg2022RegressionDD,
  title={Regression discontinuity design with right-censored survival data},
  author={Emil Aas Stoltenberg},
  year={2022}
}
In this paper the regression discontinuity design is adapted to the survival analysis setting with right-censored data, studied in an intensity based counting process framework. In particular, a local polynomial regression version of the Aalen additive hazards estimator is introduced as an estimator of the difference between two covariate dependent cumulative hazard rate functions. Large-sample theory for this estimator is developed, including confidence intervals that take into account the… 

References

SHOWING 1-10 OF 40 REFERENCES

A counting process approach to the regression analysis of grouped survival data

Further results on the non-parametric linear regression model in survival analysis.

  • O. Aalen
  • Mathematics
    Statistics in medicine
  • 1993
Martingale residuals, originally developed for the Cox model, are introduced and their theory is developed and they are shown to be useful for judging goodness of fit and on the use of bootstrap replications for judging whether the effect of a covariate disappears over time.

On inference in parametric survival data models

The usual parametric models for survival data are of the following form. Some parametrically specified hazard rate a(s, 0) is assumed for possibly censored random life times X, . . . ,X'; one

A linear regression model for the analysis of life times.

  • O. Aalen
  • Mathematics
    Statistics in medicine
  • 1989
A linear model is suggested for the influence of covariates on the intensity function. This approach is less vulnerable than the Cox model to problems of inconsistency when covariates are deleted or

Survival and event history analysisa process point of view

An introduction to survival and event history analysis.- Stochastic processes in event history analysis.- Nonparametric analysis of survival and event history data.- Regression models.- Parametric

Asymptotic Theory for Weighted Least Squares Estimators in Aalen's Additive Risk Model.

Abstract : Let h(t/Z sub i) be the conditional hazard function for the survival time of an individual sub i given the p-dimensional covariate process Z sub i(t). This document inference for Aalen's

The partly parametric and partly nonparametric additive risk model.

Methodology for estimating the hazard factor functions when some of them are modelled parametrically while the others are left unspecified is developed, which also enables us to assess the goodness of fit of the model's parametric components.

History of applications of martingales in survival analysis.

The paper traces the development of the use of martingale methods in survival analysis from the mid 1970’s to the early 1990’s. This development was initiated by Aalen’s Berkeley PhD-thesis in 1975,

IDENTIFICATION AND ESTIMATION OF TREATMENT EFFECTS WITH A REGRESSION-DISCONTINUITY DESIGN

Ž. THE REGRESSION DISCONTINUITY RD data design is a quasi-experimental design with the defining characteristic that the probability of receiving treatment changes discontinuously as a function of one

Statistical Models Based on Counting Processes.

"Statistical Models Based on Counting Processes" may be viewed as a research monograph for mathematical statisticians and biostatisticians, although almost all methods are given in sufficient detail to be used in practice by other mathematically oriented researchers studying event histories.