Health and Retirement Study

  • Last Update:May,8,2014 Created:May,8,2014
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Title of the dataset Health and Retirement Study
Provenance of the dataset http://hrsonline.isr.umich.edu/index.html
How were the data collected/created? What was the cost? Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. Since its launch in 1992, the study has collected information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Health and Retirement Study data products are available without cost to registered users; certain Conditions of Use apply. Once you are registered, the Getting Started page will help you learn more about the data products produced by this complex study.
Data sharing policy Other
Data sharing policy

About data analysis and simulation

Type of data: Check all that apply. Use "Other" to specify other types so that we can include them in further updates. number series
Variable labels of dataset (the names of the variables) PENSION PLANS|WORK|HEALTH INSURANCE|INCOME|COGNITIVE FUNCTIONING|ASSETS|DISABILITY|PHYSICAL HEALTH AND FUNCTIONING|HEALTH CARE EXPENDITURES
Outline of data The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of more than 26,000 Americans over the age of 50 every two years. The full scope of the study is described in the publication Growing Older in America: The Health and Retirement Study; an overview is provided in our general brochure
Simulation process Typically, statistics are to be applied to find the relevance between such personal or economic status (including age, income) and health state.
Expected outcome of the process (obtained knowledge, analysis results, output of tools) Poverty is an essential cause of disease.
Anticipation for analyses/simulations other than the typical ones provided above Applied KeyGraph to find difference tendencies between healthy people and those with diabate in US. See, for example, 保々佐和子・大澤幸生:データからのシナリオマップ可視化,透析学会誌 Vol.41 No.6 pp.357-358 (2008). In the above example, we found after discussion with physicians that US people get diabate when they "love to" work hard long being seated (e.g., for using PC). This is because they eat and drink things with fat, quite unusual in Japan.

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Comments I think we should be able to enter figures with uploading PNG and JPG files.
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Sample data
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