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Lam looks at population and development in next 15 years in UN commission keynote address

Mitchell et al. find harsh family environments may magnify disadvantage via impact on 'genetic architecture'

Frey says Arizona's political paradoxes explained in part by demography

Highlights

PSC newsletter spring 2014 issue now available

Kusunoki wins faculty seed grant award from Institute for Research on Women and Gender

2014 PAA Annual Meeting, May 1-3, Boston

USN&WR ranks Michigan among best in nation for graduate education in sociology, public health, economics

Next Brown Bag

Monday, April 21
Grant Miller: Managerial Incentives in Public Service Delivery

Demographic Analysis of Longitudinal Historical Data

a PSC Research Project

Investigators:   George C. Alter, Susan Hautaniemi Leonard

This project will provide extremely valuable specialized training in historical demographic techniques for analyzing longitudinal data to students and researchers working in a variety of demographic sub-fields. The rational for the project is simple: Historical demography has a long history of important contributions to the theory, methods, and practice of population studies, especially in the use of longitudinal data. Historical demographers are currently making important contributions to mainstream demographic research in fertility, mortality, family systems, aging, and migration. Indeed, the size, scope, and temporal and geographic coverage of databases currently available and under construction are unprecedented. Since historical data are often longitudinal and multi-level, they raise subtle methodological problems. Meaningful analysis often requires specialized methodologies, such as family reconstitution and back projection, that are unique to historical research. Since they are based on fundamental principles of demographic theory, students trained in these methods are both prepared for historical research and better able to use complex contemporary sources. Historical data can be a perfect model for analysis of demographic processes. The number of observed covariates is usually limited, and historical demographers have excelled in creatively using longitudinal and genealogical information to construct contextual and time-varying covariates. The longitudinal analysis techniques students learn will provide a roadmap for use with any data set with a time dimension, including many large contemporary data sets collected through NIH funding. This program will offer both formal courses and opportunities for practical experience with active researchers. Students will be introduced to data sets and advanced statistical techniques at the forefront of current research.

Funding Period: 02/14/2009 to 04/30/2014

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