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Related Concept Videos

Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and Cox...
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Related Experiment Video

Updated: May 28, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Enhancing population-wide administrative data to better understand mortality risk in underserved groups.

Emma Ross1, Sarah McKenna1, Aideen Maguire1

  • 1Administrative Data Research Centre Northern Ireland (ADRC NI), Queen's University Belfast, Belfast, Northern Ireland, United Kingdom.

SSM - Population Health
|May 27, 2026
PubMed
Summary

Population-wide data reveals that most underserved groups (USGs) have lower mortality risks. However, lesbian, gay, bisexual, and other sexual minorities (LGB+) face elevated risks for deaths of despair.

Keywords:
Administrative dataEthnic minoritiesHealth inequalitiesLGB+MortalityUnderserved groups

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Establishing a Competing Risk Regression Nomogram Model for Survival Data
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Published on: October 23, 2020

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Last Updated: May 28, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

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Published on: January 8, 2020

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Area of Science:

  • Public Health
  • Epidemiology
  • Sociology

Background:

  • Underserved groups (USGs) experience significant health disparities.
  • Studying USGs is challenging due to small sample sizes and low participation in voluntary studies.
  • Population-wide Census data offers a valuable resource for studying USGs' health outcomes.

Purpose of the Study:

  • To examine mortality outcomes among various USGs in Northern Ireland.
  • To leverage Census-linked mortality data for a comprehensive analysis.
  • To understand the heterogeneity of mortality risks within USGs.

Main Methods:

  • A population-wide cohort study using the Northern Ireland Mortality Study 2021.
  • Linking Census data to death records for individuals aged ≥16 years (n=1,463,459).
  • Cox proportional hazards models were used to analyze all-cause mortality, avoidable mortality, and deaths of despair, adjusting for sociodemographic and health factors.

Main Results:

  • 28.3% of the cohort belonged to at least one USG.
  • Most USGs (ethnic minorities, migrants, limited English, religious minorities) showed lower all-cause mortality risk.
  • Lesbian, gay, bisexual, and other sexual minorities (LGB+) had elevated risk for deaths of despair (HR 1.21, 95% CI 1.02-1.43) after full adjustment.

Conclusions:

  • Most USGs exhibited lower mortality risks compared to their reference populations.
  • LGB+ individuals demonstrated an elevated risk for deaths of despair.
  • Population-wide data is crucial for understanding diverse mortality patterns among USGs.