Health and Retirement Study

  • 作成日:2014年05月08日 最終更新日:2014年05月08日
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提出者情報

データジャケットの題名 Health and Retirement Study
データの所在・所有者 http://hrsonline.isr.umich.edu/index.html
データ収集方法やコスト 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.
データの共有について その他
データの共有について (その他を選ばれた方)

データの分析・シミュレーションについて

データの種類 数値 時系列
データの変数(パラメーター)の変数名 PENSION PLANS|WORK|HEALTH INSURANCE|INCOME|COGNITIVE FUNCTIONING|ASSETS|DISABILITY|PHYSICAL HEALTH AND FUNCTIONING|HEALTH CARE EXPENDITURES
データの概要説明 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
想定しているデータの分析・シミュレーションプロセス Typically, statistics are to be applied to find the relevance between such personal or economic status (including age, income) and health state.
想定しているデータの分析・シミュレーションプロセスの結果 (データ分析結果/ツールの出力/典型例など) Poverty is an essential cause of disease.
上記の分析・シミュレーションプロセス以外に期待する分析 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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自由記述 I think we should be able to enter figures with uploading PNG and JPG files.
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