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Related Concept Videos

Applications of Life Tables01:22

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Levels of Health Promotion and Illness Prevention01:26

Levels of Health Promotion and Illness Prevention

Health promotion allows a person to control the determinants of health, resulting in an improved health status. It enhances the quality of life and reduces premature deaths. Health promotion and illness prevention programs help people make beneficial choices to reduce the risk of disease and disabilities. There are three health promotion and illness prevention levels: primary, secondary, and tertiary prevention.
In primary prevention, actions taken before disease onset prevent the disease from...
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

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.
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,...
Truncation in Survival Analysis01:09

Truncation in Survival Analysis

Truncation in survival analysis refers to the exclusion of individuals or events from the dataset based on specific criteria related to the time of the event. This exclusion can happen in two primary forms: left truncation and right truncation.
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are observed.

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Related Experiment Video

Updated: May 10, 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

Welfare programs that target workforce participation may negatively affect mortality.

Peter Muennig1, Zohn Rosen, Elizabeth Ty Wilde

  • 1Columbia University, New York, NY, USA. pm124@columbia.edu

Health Affairs (Project Hope)
|June 5, 2013
PubMed
Summary

US welfare reform, which included time limits, was associated with a 16% increase in mortality among participants. This study questions the long-term health impacts of such social policies.

Keywords:
Determinants Of Health

Related Experiment Videos

Last Updated: May 10, 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

Area of Science:

  • Public Health
  • Social Policy
  • Health Economics

Background:

  • US welfare reforms in the 1990s introduced time limits to encourage employment among public assistance recipients.
  • The long-term health consequences of these welfare reform programs remain largely unknown.
  • Understanding the impact of social policies on participant health is crucial for public well-being.

Purpose of the Study:

  • To investigate the long-term effects of the Florida Family Transition Program (FFTP) on participant mortality.
  • To determine if welfare reform experiments, like the FFTP, lead to significant changes in mortality rates.
  • To assess the health implications of welfare-to-work policies.

Main Methods:

  • A randomized trial involving 3,224 participants in the Florida Family Transition Program.
  • Prospective mortality follow-up data collected over 17-18 years.
  • Comparison of mortality rates between FFTP participants and recipients of traditional welfare.

Main Results:

  • Participants in the Florida Family Transition Program experienced a 16% higher mortality rate compared to those receiving traditional welfare.
  • The FFTP involved a 24-36 month time limit for welfare, job training, and placement assistance.
  • A significant association was found between participation in this welfare reform program and increased long-term mortality.

Conclusions:

  • The findings suggest that welfare reform programs with time limits may have adverse long-term health outcomes, specifically increased mortality.
  • If generalizable, these results challenge the justification of cost savings from welfare reform against the societal cost of increased mortality.
  • Further research is needed to understand the mechanisms linking welfare reform policies to mortality and to evaluate the overall societal impact.