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Related Concept Videos

Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Longitudinal Studies01:26

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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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Cross-Sectional Research01:50

Cross-Sectional Research

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In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
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Applications of Life Tables01:22

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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...
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Population Growth00:57

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Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
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Jeffrey Arnett's concept of emerging adulthood offers a framework to understand the unique developmental stage between adolescence and full-fledged adulthood, generally from ages 18 to 25. This period is marked by extensive exploration and shifts in identity, relationships, and career choices, a process known in psychology as role experimentation. Emerging adulthood reflects the evolving cultural expectations surrounding adulthood and the dynamic process of personal transformation during...
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The pig in the python: US decennial labor flows and economic opportunity, 1910-2040.

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The IPUMS Multigenerational Longitudinal Panel: Progress and Prospects.

Steven Ruggles1, Julia A Drew2, Catherine A Fitch2

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Summary
This summary is machine-generated.

The IPUMS Multigenerational Longitudinal Panel (MLP) links historical U.S. data from 1850 to present. This infrastructure enables new research on long-term demographic and social trends.

Keywords:
CensusIPUMSRecord Linkagelongitudinal data

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Area of Science:

  • Demography
  • Sociology
  • Historical Research
  • Data Science

Background:

  • Longitudinal population data is crucial for understanding societal changes over time.
  • Existing datasets often lack comprehensive, long-term linkages across diverse sources.
  • The need for an integrated, high-quality longitudinal panel for American population studies is evident.

Purpose of the Study:

  • To introduce the IPUMS Multigenerational Longitudinal Panel (MLP) as a novel resource.
  • To detail the infrastructure, linking methodologies, and future development plans for MLP.
  • To showcase the potential of MLP for advancing research in social sciences and demography.

Main Methods:

  • Constructing the MLP by linking American censuses, surveys, administrative records, and vital statistics from 1850 to the present.
  • Utilizing advanced record linkage techniques to ensure data accuracy and integrity.
  • Developing a robust technological infrastructure for data management and accessibility.

Main Results:

  • The establishment of a comprehensive longitudinal population panel spanning over 170 years.
  • Successful integration of diverse historical data sources into a unified dataset.
  • Demonstration of early research applications utilizing the MLP, highlighting its utility.

Conclusions:

  • The IPUMS MLP provides an unparalleled resource for multigenerational and historical population research.
  • Future expansion plans, including a "linkage hub," will further enhance MLP's connectivity and research potential.
  • MLP is poised to facilitate significant advancements in understanding long-term social and demographic dynamics in the United States.