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Found 7 result(s)

Longitudinal Aging Study Amsterdam

LASA

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The Longitudinal Aging Study Amsterdam (LASA) at the VU University and VU University Medical Centre is initiated by the Ministry of Health, Welfare and Sports in 1991 to determine predictors and consequences of ageing. LASA focuses on, physical, emotional, cognitive and social functioning in late life, the connections between these aspects, and the changes that occur in the course of time

TRAILS

Tracking Adolescents' Individual Lives Survey

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TRAILS is a prospective cohort study, which started in 2001 with population cohort and 2004 with a clinical cohort (CC). Since then, a group of 2500 young people from the Northern part of the Netherlands has been closely monitored in order to chart and explain their mental, physical, and social development. These TRAILS participants have been measured every two to three years, by means of questionnaires, interviews, and all kinds of tests. By now, we have collected information that spans the total period from preadolescence up until young adulthood. One of the main goals of TRAILS is to contribute to the knowledge of the development of emotional and behavioral problems and the (social) functioning of preadolescents into adulthood, their determinants, and underlying mechanisms.

ICTWSS database

Database on Institutional Characteristics of Trade Unions, Wage Setting, State Intervention and Social Pacts in 51 countries between 1960 and 2014

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The ICTWSS database covers four key elements of modern political economies: trade unionism, wage setting, state intervention and social pacts. The database contains annual data for all OECD and EU member states - Australia; Austria; Belgium; Bulgaria; Canada; Chile, Cyprus, the Czech Republic; Denmark; Estonia; Germany; Greece; Finland; France; Hungary; Iceland; Ireland; Israel, Italy; Japan; Korea, Latvia; Lithuania; Luxembourg; Malta; Mexico; the Netherlands; New Zealand; Norway; Poland; Portugal; Romania; Spain; Slovakia; Slovenia; Sweden; Switzerland; Turkey; the United Kingdom; and the United States – with some additional data for emerging economies Brazil; China; India; Indonesia; Russia; and South Africa; and it runs from 1960 till 2014.

Maddison Project

Maddison Historical Statistics

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Maddison's work contains the Project Dataset with estimates of GDP per capita for all countries in the world between 1820 and 2010 in a format amenable to analysis in R. The database was last updated in January 2013. The update incorporates much of the latest research in the field, and presents new estimates of economic growth in the world economic between AD 1 and 2010 The Maddison Project database presented builts on Angus Maddison's original dataset. The original estimates are kept intact, and only revised or adjusted when there is more and better information available. Angus Maddison's unaltered final dataset remains available on the Original Maddison Homepage https://www.rug.nl/ggdc/historicaldevelopment/maddison/original-maddison

World Religion Database

WRD

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The World Religion Database (WRD) contains detailed statistics on religious affiliation for every country of the world. It provides source material, including censuses and surveys, as well as best estimates for every religion to offer a definitive picture of international religious demography. It offers best estimates at multiple dates for each of the world’s religions for the period 1900 to 2050.

World Christian Database

WCD

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The World Christian Database provides comprehensive statistical information on world religions, Christian denominations, and people groups. The World Christian Database transforms current religious statistics into a real-time analysis tool that takes just minutes to perform even detailed research. This comprehensive database brings together a fully updated and cohesive religious data set with a world-class database architecture. The result is a simple, yet powerful database tool that enables users to customize reports and download data for in use in charts, tables, and graphs

OpenML

Open Machine Learning

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OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.