Mark Handcock

Ph.D. 1989, University of Chicago. Economic inequality, statistical methods for social science.

Department: Statistics
Position: Professor
Email: click here
Phone: (206)543-6774, (206) 616-6235
Box: 354332
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Research Summary:

Mark S. Handcock is a professor and the chair of statistics and sociology at the University of Washington. Over the past three years, he has worked on three longstanding research interests: innovative statistical methodology for demographic research, trends in earnings inequality, and the interaction between population and the environment. Handcock is a statistician by training and his work is primarily methodological development. However the motivations for this research are demographic questions.

Recent examples of work important for scientific research are the development of statistical models for the analysis of longitudinal data on job mobility, wage trajectories and distributional changes in earnings. He is also currently working on statistical modeling of social networks with particular emphasis on the spread of HIV. An important aspect of this work is the design and analysis of survey sampling for social networks, and sex/intravenous drug user networks in particular.

Handcock is a leader in the field of distributional comparisons. In demographic research, differences among groups or changes over time are a common focus of study. While means and variances are typically the basis for the methods used in this research, the underlying social theory often implies properties of distributions, such as comparisons of changes in the upper and lower tails, that are not well captured by these summary measures. Handcock has developed innovative methodology that enables researchers to conduct detailed analyses of distributional difference. The framework is based on the relative distribution, which provides a graphical display that simplifies exploratory data analysis, a statistically valid basis for the development of hypothesis-driven summary measures, and location, shape, and covariate decompositions that identify the sources of distributional changes within and between groups. With Martina Morris, he has published a research monograph, Relative Distribution Methods in the Social Sciences (1999), detailing the methods and has made a program freely available for use by researchers worldwide.

Handcock has also made contributions to inequality research as part of collaborative teams. Along with Martina Morris and other colleagues, he has 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.

Handcock is also an accomplished researcher in environmetrics, where he focuses on spatial statistics and inference for stochastic processes. Recent applications have been the analysis of the spatial-temporal variation in earnings polarization in U.S. counties and models for combining information from multiple environmental surveys with remote sensing data within a GIS. Much of this work is in the area of population and environment: perspectives that stress the importance of interactions between social and physical environmental processes. There is also substantial intellectual exchange between this work and demographic work. An example is the development of models for combining individual-level survey data and population-level information to better address demographic questions.

He is the coordinator of the population and the environment core of the National Research Center for Statistics and the Environment and a core faculty member at the Center for Statistics and the Social Sciences (both at UW).

Handcock, M.; Gile, K. J., (Forthcoming), Modeling Networks from Sample Data, Annals of Applied Statistics: Special Section on Network Modeling.

Handcock, M.; Morris, M.; Borgatti, S., (Forthcoming), Statistical Modeling of Social Networks, 256, Springer-Verlag, New York.

Rendall, M. S.; Handcock, M. S.; Jonsson, S. H., (2009), Bayesian Estimation of Hispanic Fertility Hazards from Survey and Population Data, Demography, 46: 1, 65-82.

van Duijn, M. A. J.; Gile, K. J.; Handcock, M. S., (2009), A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models, Social networks., 31: 1, 52.

Admiraal, R.; Handcock, M. S., (2008), networksis: A Package to Simulate Bipartite Graphs with Fixed Marginals Through Sequential Importance Sampling, Journal of Statistical Software, 24: 8.

Chaudhuri, S.; Handcock, M. S.; Rendall, M. S., (2008), Generalized linear models incorporating population level information: an empirical-likelihood-based approach, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70: 2, 311-328.

Goodreau, S. M.; Handcock, M. S.; Hunter, D. R.; Butts, C. T.; Morris, M., (2008), A statnet Tutorial, Journal of Statistical Software, 24: 9.

Handcock, M. S.; Glynn, A.; Wakefield, J.; Richardson, T., (2008), Alleviating Linear Ecological Bias and Optimal Design with Subsample Data, Journal of the Royal Statistical Society: Series A.

Handcock, M. S.; Hamilton, D.; Morris, M., (2008), Degree distributions in sexual networks: A framework for evaluating evidence, Sexually Transmitted Infections.

Handcock, M. S.; Hunter, D. R.; Butts, C. T.; Goodreau, S. M.; Morris, M., (2008), Statnet: software tools for the representation, visualization, analysis and simulation of social network data, Journal of Statistical Software, 24: 3.

Handcock, M. S.; Morris, M., (2008), A curved exponential family model for complex networks, Computational and Mathematical Organization Theory.

Hunter, D. R.; Goodreau, S. M.; Handcock, M. S., (2008), Goodness of Fit of Social Network Models, Journal of the American Statistical Association., 103: 481, 248.

Hunter, D. R.; Handcock, M. S.; Butts, C. T.; Goodreau, S. M.; Morris, M., (2008), Ergm: a package to fit, simulate and diagnose exponential-family models for networks, Journal of Statistical Software, 24: 3.

Morris, M.; Handcock, M. S.; Hunter, D. R., (2008), Specification of Exponential-Family Random Graph Models: Terms and Computational Aspects, Journal of Statistical Software, 24: 4.

Pavel N. Krivitsky; Handcock, M. S., (2008), Fitting Latent Cluster Models for Networks with latenet, Journal of Statistical Software, 24: 5.

Rendall, M.; Admiraal, R.; DeRose, A.; DiGiulio, P.; Handcock, M.; Racioppi, F., (2008), Population constraints on pooled surveys in demographic hazard modeling, Statistical Methods and Applications, 17: 4, 519-539.

Handcock, M., (2007), Model-based combination of spatial information for stream networks, Environmental and Ecological Statistics, 14: 3, 267-284.

Handcock, M. S.; Raferty, A. E.; Tantrum, J., (2007), Model-Based Clustering for Social Network, Journal of the Royal Statistical Society: Series A, 170: 2, 301-354.

Rendall, M. S.; Handcock, M. S.; Jonsson, S. H., (2007), Bayesian estimation of Hispanic fertility hazards from survey and population data, RAND, Santa Monica, CA.

Robins, G.; Handcock, M. S.; Snijders, T.; Wang, P.; Pattison, P., (2007), Recent developments in exponential random graph (p*) models for social networks, Social Networks, 29: 2, 192.

Handcock, M. S.; Jones, J. H., (2006), Interval estimates for epidemic thresholds in two-sex network models, Theoretical Population Biology, 70: 2, 125.

Handcock, M. S.; Shortreed, S.; Hoff, P., (2006), Positional Estimation within the Latent Space Model for Networks, Methodology, 2: 1, 24-33.

Hunter, D. R.; Handcock, M. S., (2006), Inference in Curved Exponential Family Models for Networks, Journal of Computational and Graphical Statistics, 15: 3, 565.

Morris, M.; Handcock, M. S.; Miller, W. C.; Ford, C. A.; Schmitz, J. L.; Hobbs, M. M.; Cohen, M. S.; Harris, K. M.; Udry, J. R., (2006), Prevalence of HIV Infection Among Young Adults in the United States: Results From the Add Health Study, American Journal of Public Health, 96: 6, 1091.

Handcock, M. S.; Rendall, M. S.; Cheadle, J. E., (2005), Improved Regression Estimation of A Multivariate Relationship with Population Data on the Bivariate Relationship, Sociological Methodology, 35: 1, 303.

Kerani, R. P., et al, ; Handcock, M. S., (2005), Comparative Geographic Concentrations of Four Sexually Transmitted Infections, American Journal of Public Health, 95: 2, 342-330.

Miller, W. C.; Swygard, H.; Hobbs, M. M.; Ford, C. A.; Handcock, M. S.; Morris, M.; Schmitz, J. L.; Cohen, M. S.; Harris, K. M.; Udry, J. R., (2005), The prevalence of trichomoniasis in young adults in the United States, Sexually Transmitted Diseases, 32: 10, 593-598.

Scott, M. A.; Handcock, M. S., (2005), Persistent Inequality? Answers from Hybrid Models for Longitudinal Data, Sociological Methods and Research, 32: 3, 394-424.

Snijders, T. A. B.; Pattison, P. E.; Robins, G. L.; Handcock, M. S., (2005), New specifications for exponential random graph models, Sociological Methodology, 35.

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