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Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
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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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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...
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Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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ADAPTATION TO POVERTY IN LONG-RUN PANEL DATA.

Andrew E Clark1, Conchita D'Ambrosio2, Simone Ghislandi3

  • 1Paris School of Economics and CNRS.

The Review of Economics and Statistics
|July 11, 2017
PubMed
Summary

Poverty significantly lowers life satisfaction, and individuals do not appear to adapt to being poor over time. This study examines subjective well-being and poverty duration in Germany.

Area of Science:

  • Social Sciences
  • Economics
  • Psychology

Background:

  • Poverty is a significant social issue with potential impacts on individual well-being.
  • Adaptation to adverse conditions is a known human psychological response.
  • Understanding the long-term effects of poverty on subjective well-being is crucial for policy development.

Purpose of the Study:

  • To investigate the relationship between poverty and subjective well-being.
  • To examine the extent to which individuals adapt to poverty over time.
  • To identify factors influencing adaptation to poverty.

Main Methods:

  • Utilized longitudinal panel data from nearly 54,000 individuals in Germany (1985-2012).
  • Employed statistical analysis to assess the impact of poverty incidence and intensity on life satisfaction.

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  • Analyzed changes in subjective well-being within poverty spells to detect adaptation.

    • Main Results:

    • Life satisfaction demonstrably decreases with both the onset and severity of poverty.
    • Evidence for adaptation to poverty within a poverty spell is minimal.
    • Subjective well-being remains consistently low during poverty episodes.

    Conclusions:

    • Poverty has a persistent negative effect on subjective well-being.
    • Individuals do not significantly adapt their well-being to prolonged poverty.
    • Further research is needed to understand the causes behind the lack of poverty adaptation.