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Related Concept Videos

Hazard Rate01:11

Hazard Rate

The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
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Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
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Additive and multiplicative hazards modeling for recurrent event data analysis.

Hyun J Lim1, Xu Zhang

  • 1Department of Community Health & Epidemiology College of Medicine, University of Saskatchewan, Saskatoon, Canada. hyun.lim@usask.ca

BMC Medical Research Methodology
|June 29, 2011
PubMed
Summary
This summary is machine-generated.

Analyzing recurrent event data in biomedical studies, this research compares additive and multiplicative hazards models. Both models effectively identified risk factors, but the additive model offered narrower confidence intervals for recurrent events.

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Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Area of Science:

  • Biostatistics
  • Epidemiology
  • Health Services Research

Background:

  • Biomedical longitudinal studies frequently yield sequentially ordered multivariate failure time or recurrent event duration data.
  • Standard hazard regression methods are inadequate for this data due to within-subject correlation and dependent censoring.
  • Multiplicative and additive hazards models offer frameworks for analyzing risk factor associations in recurrent event data.

Purpose of the Study:

  • To illustrate and compare the performance of additive and multiplicative hazards models for recurrent event duration analysis.
  • To evaluate these models under varying baselines with common and order-specific coefficient effects.
  • To analyze emergency department visit data to demonstrate model application.

Main Methods:

  • Application of both additive and multiplicative hazards models to emergency department visit data.
  • Comparison of model results under scenarios with a varying baseline and common coefficient effects.
  • Comparison of model results under scenarios with a varying baseline and order-specific coefficient effects.

Main Results:

  • Both models yielded similar covariate selections when using a varying baseline with common coefficient effects.
  • The multiplicative hazards model exhibited wider confidence intervals compared to the additive hazards model for recurrent events.
  • Confidence intervals widened with increasing revisit order in both models due to a decreasing risk set.

Conclusions:

  • Additive and multiplicative hazards models are broadly applicable to recurrent event data common in clinical and epidemiologic studies.
  • These models provide distinct, complementary information rather than serving as alternatives.
  • Using both models together offers a more comprehensive understanding of recurrent event data.