Home > People > U-M Researchers . Off-Campus . Training . Postdocs . Predocs . Staff . Experts . Disciplines

PSC In The News

RSS Feed icon

Cheng finds marriage may not be best career option for women

Lam discusses youth population dynamics and economics in sub-Saharan Africa

Work by Bailey and Dynarski cited in NYT piece on income inequality


Jeff Morenoff makes Reuters' Highly Cited Researchers list for 2014

Susan Murphy named Distinguished University Professor

Sarah Burgard and former PSC trainee Jennifer Ailshire win ASA award for paper

James Jackson to be appointed to NSF's National Science Board

Next Brown Bag

PSC Brown Bags will return in the fall

Ge Lin photo

Email Address
402 559-2953

Ge Lin

Associate Professor, Health Services Research & Administration, University of Nebraska.

Off-Campus Research Affiliate, Population Studies Center.

Ph.D., State University of New York-Buffalo

Dr. Lin is an expert in Geographic Information Systems, and specializes in research on U.S. migration, geography of aging and health, and their interactions with the environment.

Recent Publications

Journal Articles

Keyes, Katherine M., John E. Schulenberg, Patrick M. O'Malley, Lloyd Johnston, Jerald Bachman, Ge Lin, and Deborah Hasin. 2011. "The social norms of birth cohorts and adolescent marijuana use in the United States, 1976-2007." Addiction, 106(10): 1790-1800. PMCID: PMC3174352. DOI. Abstract.

Keyes, K.M., Rebecca L. Utz, W. Robinson, and Ge Lin. 2010. "What is a cohort effect? Comparison of three statistical methods for modeling cohort effects in obesity prevalence in the United States, 1971-2006." Social Science & Medicine, 70(7): 1100-1108. DOI. Abstract.

Banasick, S., Ge Lin, and R. Hanham. 2009. "Deviance Residual Moran's I Test and Its Application to Spatial Clusters of Small Manufacturing Firms in Japan." International Regional Science Review, 32(1): 3-18. DOI. Abstract.

Lin, Ge, G. Elmes, M. Walnoha, and X.N. Chen. 2009. "Developing a Spatial-Temporal Method for the Geographic Investigation of Shoeprint Evidence." Journal of Forensic Sciences, 54(1): 152-158. DOI. Abstract.

Lin, Ge, and T.L. Zhang. 2007. "Loglinear residual tests of Moran's I autocorrelation and their applications to Kentucky breast cancer data." Geographical Analysis, 39:293-310. DOI. Abstract.

View additional select publications of Ge Lin