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 additive risk model h(t/Z sub i)=Z sub i(t) alpha (t), where alpha is a p-vector of unknown hazard functions. The theory of counting processes is used to obtain weak convergence results for weighted least squares estimators of the hazard functions and the cumulative hazard functions based on continuous data. Results for weighted least squares estimators based on grouped data are also described. Keywords: Regression models, Biostatistics.

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1987
Accession Number
ADA191085

Entities

People

  • Ian W. Mckeague

Organizations

  • Florida State University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Additives (Chemicals)
  • Biostatistics
  • Convergence
  • Covariance
  • Data Science
  • Information Science
  • Kernel Functions
  • Mathematics
  • Probability
  • Regression Analysis
  • Security
  • Statistical Algorithms
  • Statistical Inference
  • Statistics
  • Stochastic Processes
  • Survival
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms