Archives: Affiliates

Gary Chan’s research interests include survival analysis and stochastic processes, epidemiological design and analysis, missing data and causal inference, nonlinear mixed models and predictions, and semiparametric models.

Jennifer Otten is a Professor in Environmental and Occupational Health Sciences and affiliated with the Nutritional Sciences Program and UW Center for Public Health Nutrition. Dr. Otten received her BS in Nutritional Sciences from Texas A&M University, her MS in Nutrition Communications from Tufts University, her PhD in Animal, Nutrition, and Food Sciences from the University of Vermont, and completed a postdoctoral research fellowship at the Stanford Prevention Research Center in the Stanford University School of Medicine. She completed her dietetic internship at Massachusetts General Hospital, Boston. Between 1998-2006, Dr. Otten served in various capacities for the Institute of Medicine of the National Academy of Sciences in Washington D.C., including as a study director and as the organization’s first communications director.

Her research interests include the impacts of public health, nutrition, and food policies and the policy process on health behaviors and health outcomes; food systems, as it relates to food and nutrition policy; and understanding and improving the ways in which research gets to the public policy table.

 

Rachel Fyall joined the Evans School of Public Policy and Governance as an assistant professor beginning Autumn 2014. Her research investigates the influence of nonprofit organizations on the formation of public policy and in the delivery of public services. She examines how discretion shapes the public services provided by nonprofit contractors as well as advocacy and lobbying by nonprofit organizations. Her primary research context is publicly subsidized low-income housing, including the Low-Income Housing Tax Credit program and various homelessness interventions. Rachel’s research has been published in Public Administration Review, Policy Studies Journal, and Nonprofit and Voluntary Sector Quarterly. She is a faculty affiliate of the West Coast Poverty Center and the Center for Studies in Demography and Ecology, both at UW.

Rachel holds a Ph.D. in Public Affairs from Indiana University, an M.P.A. from George Washington University (nonprofit management concentration), and a B.A. in Sociology and Latin American Studies from Wesleyan University. Before pursuing her doctorate, Fyall worked in housing policy at the Housing Development Consortium in Seattle. She previously worked at the Technology Access Foundation (Seattle) and has professional and volunteer experience in a variety of other nonprofit organizations.

Martina Morris is a Professor Emeritus of sociology and statistics at the University of Washington. Over the past three years, she has worked on three longstanding research interests: the demographic epidemiology of HIV, trends in earnings inequality, and innovative statistical methodology for demographic research.

Morris’ HIV related research is now internationally recognized. She was one of the pioneers in the field of network epidemiology, and her recent research remains at the forefront of the field. In a series of recent papers, she has documented the importance of concurrent partnerships in amplifying the transmission dynamics of HIV, quantified the impact of date measurement error in survey estimates of concurrency, and used microsimulation to estimate the impact of concurrency on HIV transmission in Uganda. Morris specializes in the development of statistical methodology for estimating epidemiologically critical network parameters from “local network” study designs. Local network studies use traditional sample survey techniques, enrolling randomly selected respondents, and asking them to report on their partner’s attributes and behaviors. This approach is much less expensive and intrusive than other network study designs that require eliciting, tracing, and enrolling partners. Morris organized an international conference on demographic network survey design in February 2000, sponsored by the IUSSP.

Morris’ work on inequality is also well recognized. She and her colleagues have just completed a five-year project comparing long-term economic mobility for white men before and after the economic restructuring of the 1980s and 1990s. Using the two cohorts of the NLS, they are the first to have documented that the growing inequality in cross-sectional earnings distributions is being driven by a growing segregation of wage profiles, and a greater “stickiness” in low-wage careers. Their findings are contained in the recently published book Divergent Paths (2001). This project also resulted in a number of careful detailed analyses that challenged conventional wisdom regarding trends in job instability, the quality of the NLS data, and the relative size of transient and permanent variation in age-earnings profiles.

In the course of this substantive research, Morris has also developed new statistical methodology in a number of areas. She has developed extensions to generalized linear models for local network analysis and innovative epidemiologically relevant network summary measures. With Mark Handcock, she has developed a new statistical framework for distributional comparison, published as a book, Relative Distribution Methods in the Social Sciences (1999).

Ali Modarres specializes in urban planning and public policy with a focus on the socio-spatial dynamics of American cities. Since the late 1980s, his research has centered on issues related to access for immigrants and minority communities in the U.S. A significant level of this research has relied on in-depth analysis of macro and micro geographies of poverty, demographic shifts, and the changing structure of urban services, including transportation, employment geography, and housing.

He is the co-Editor of the Journal of Race, Ethnicity, and the City.

Tyler McCormick’s research has been devoted to two themes: how to develop statistical methods to learn about social network structure using sampled or partially observed network data; and how to leverage social structure in social networks to access populations that are excluded from the sampling frame of most surveys (the homeless, or individuals living with HIV, for example). McCormick’s work on statistical methods have focused primarily on “How many X’s do you know?’’ data. In such data, respondents report the number of ties they have with members of a particular population, X. These data require no special sampling mechanism and are easily incorporated into standard surveys. McCormick has used these data to produce estimates of features of respondents’ local networks and of global network properties. He has published papers on estimating respondents’ degrees, the population degree distribution, and levels of overdispersion (excess variation in the data due to social structure). McCormick’s most recent work in this area is a new class of statistical models based on latent space models proposed in the complete network literature. These models estimate relative homogeneity between groups in the population and variation in the propensity for interaction between respondents and group members. McCormick has also worked extensively on data collection issues for these data, suggesting strategies for more efficient survey design and proposing statistical adjustments for common forms of respondent error. McCormick’s work on hard-to-reach populations proposes network-based estimates for the demographic profiles of these populations. This project also let to survey design recommendations for future data collection. He has published on these topics in the Journal of the American Statistical Association and the American Journal of Sociology.

Jonathan Mayer’s research over the past decade has been in several directions, most broadly in the area of the ecology of human disease: how biology, environment, and society interact to produce states of health and disease. Epidemiology, ecology, and spatial analysis of infectious diseases, especially pertaining to developing countries; the epidemiology of pain; urban slum health in developing countries; tuberculosis and HIV/AIDS in sub-Saharan Africa; host-environment interaction in infectious disease pathogenesis; water, sanitation, and infectious disease; and global environmental change and health, beginning with his membership on the Institute of Medicine/National Academy of Sciences joint Committee on Climate, Ecosystem Change, Infectious Diseases, and Human Health, which was tasked with ascertaining the state of knowledge on the relations between climate variability and infectious diseases. He has served on numerous NAS and NIH panels and committees, including the NAS Standing Committee on the Geographical Sciences; and the Committee on Research Priorities in the Earth Sciences and Public Health; and a committee that is joint between NIH and the Association of American Geographers dealing with the development of a cross-institute initiative on developing a GIScience infrastructure at NIH.

Mayer has published in journals including JAMA; Spine; Anesthesiology; Interdisciplinary Perspectives on Infectious Diseases; Social Science and Medicine; and Progress in Human Geography; and the Clinical Journal of Pain. He has published numerous book chapters on the health effects of migration; health effects of natural disasters; and “epidemiologic geography,” which is a term that he coined to reflect the current state of his field in a recent publication.

Currently, Mayer is working on several COVID-19 projects, as well as various projects involving the epidemiology of pain and pain treatment.

Ross L. Matsueda’s research interests include criminology, juvenile delinquency, deviance, teen childbearing, statistics, methods, and social psychology. He has been involved with two major research projects over the last decade. The first, funded by NIH and in collaboration with Erosheva, Social Work, Kreager, Penn State, and Telesca, UCLA, examines life course trajectories of substance use and crime. On the methodological side, after showing tha latent class mixture models of trajectories fit individual trajectories poorly, they develop an alternative model that assumes a single age-crime curve, and then estimates departures from that curve using individual-specific parameters of phase (to model onset and desistance) and amplitude (to model level of offending). They model the age crime curve using B-splines, and factor out individual-specific temporal misalignment and amplitude via Bayesian curve registration methods. The initial paper in this series received a revise and resubmit at the JASA. On the substantive side, Matsueda is examining the effects of life course transitions, such as the transition to parenthood, marriage, college, and employment, on substance use and crime. An initial paper using fixed-effects models found support for the hypothesis, identified in ethnographic research, that that within disadvantaged neighborhoods, motherhood can result in a positive transformation of previously delinquent and chaotic lives. The next step will be to examine the effects of fatherhood, which appear to operate very differently from motherhood, and examine whether these results hold for the nation as a whole, or only a disadvantaged subgroup, as suggested by ethnographic studies. Matsueda is also examining the long-term effects (on criminality and socioeconomic outcomes) of parenting during childhood and working during adolescence. A second project, funded by NSF, examines the spatial distribution of crime and violence across Seattle neighborhoods. This project tests social capital and collective efficacy theories using data collected on 5,000 Seattle residents within 123 census tracts.