Project Summary/Abstract This project uses archival data from the three primary National Longitudinal Survey of Youth (NLSY) datasets to create new data structures, to maintain and distribute those data structures to other research teams, and to conduct research. The project is designed to use sophisticated data management and statistical methods to develop new kinship linking structure in the NLSY97; to match portions of the NLSY79, NLSYC/YA, and NLSY97 datasets; to market and circulate data and provide user service support to researchers in behavior genetics, family studies and demography, developmental psychology, economics, and other disciplines who use the NLSY family structure; and to conduct sophisticated empirical analyses using the kinship links and dataset matches. These projects take advantage of our 20+ years of past experience defining and using kinship links in the NLSY files, and in particular extend an earlier NIH funded research project that has focused on the NLSY79 and NLSYC/YA datasets. The product of the proposed research will be both online and e-mail release of NLSY kinship links, files with dataset matches, as well as open-source coding and algorithms and vignettes illustrating the use of these resources in research and computing environments. These activities are associated with the first two years of the proposed project. In year 1.5-3.0, we will conduct empirical research projects in several studies that take advantage of the newly-developed NLSY data structures to study cognitive development and fertility outcomes.

Narrative This project involves creating, validating, and circulating new data resources by using three National Longitudinal Survey of Youth datasets, the NLSY79, the NLSY-Children, and the NLSY97. Kinship links to support behavior genetic, demographic, lifespan developmental, aging, and other family researchers are completed for the three dataset by filling those in for the NLSY97 (links for the other two datasets were completed in past research), and the three datasets are matched using two different methodologies to support sophisticated and innovative research designs. We ultimately use these new family indicators in two empirical research projects, one that models cognitive development biometrically, and one that models fertility outcomes with a "proxy mother" design, each using the three NLSY datasets.