Handbook of Mixed Membership Models and Their Applications, Chapman & Hall/CRC (2014)
(co-edited with E. M. Airoldi, D. M. Blei, and S.E. Fienberg)
· E. A. Erosheva, H.-J. Kim, C. A. Emlet, and K. I. Fredriksen-Goldsen. Social Networks of Lesbian, Gay, Bisexual and Transgender Older Adults, Research on Aging (2015).
· E. A. Erosheva and C. Joutard. Estimating Diagnostic Error without Gold Standard: A Mixed Membership Approach,' Handbook on Mixed-Membership Models (E.M. Airoldi, D.M. Blei, E.A. Erosheva, and S.E. Fienberg, eds.), Chapman & Hall/CRC (2014).
· E. A. Erosheva, R. L. Matsueda, and D. Telesca. Breaking bad: Two decades of life-course data analysis in criminology, developmental psychology, and beyond. Annual Review of Statistics and Its Application (2014), 1:301-332.
· T. A. White and E. A. Erosheva. Using group-based latent class transition models to analyze chronic disability data from the National Long-Term Care Survey 1984-2004. Statistics in Medicine (2013), 32(20):3569-89.
· J. Gruhl, E. A. Erosheva, and P.K. Crane A Semiparametric Approach to Mixed Outcome Latent Variable Models: Estimations the Association Between Cognition and Regional Brain Volumes, Annals of Applied Statistics (2013):Vol.7, No.2
· D. Telesca, E. A. Erosheva, D. Kreager, and R. Matsueda. ``Modeling Criminal Careers as Departures from a Unimodal Age-Crime Curve: The Case of Marijuana Use,'' Journal of the American Statistical Association: Applications and Case Studies (2012), 107(500):1427-1440 (JASA featured article).
· E. M. Airoldi, E. A. Erosheva, S. E. Fienberg, C. Joutard, T. Love, and S. Shringarpure. Re-conceptualizing the Classification of PNAS Articles, Proceedings of the National Academy of Sciences (2010), 107(49): 20899-20904.
· E. A. Erosheva and T. A. White. Issues in survey measurement of chronic disability: An example from the National Long Term Care Survey, Journal of Official Statistics, (2010), 26(2):317-339.
· D. A. Kreager, R. L. Matsueda, and E. A. Erosheva. Motherhood and criminal desistance in disadvantaged neighborhoods Criminology (2010), 41(1), 221-258.
· E. A. Erosheva, S. E. Fienberg, and C. Joutard. Describing disability through individual-level mixture models for multivariate binary data. Annals of Applied Statistics (2007), Vol.1, No.2: 502-537.
· E. A. Erosheva, E. C. Walton, and D. T. Takeuchi. Self-rated Health among Foreign- and US-born Asian Americans: A test of Comparability. Medical Care (2007), 45(1): 80-87.
· E. A. Erosheva. Latent Class Representation of the Grade of Membership Model. Technical Report 492, Department of Statistics, University of Washington (2006).
· E. A. Erosheva. Will the market bear your asking price? Chance (2005), 18(3), 23-28.
· E. A. Erosheva. Comparing Latent Structures of the Grade of Membership, Rasch, and Latent Class Models. Psychometrika (2005),70(4), 619-628.
· E. A. Erosheva, S.E. Fienberg, and J. Lafferty. Mixed-Membership Models of Scientific Publications. Proceedings of the National Academy of Sciences (2004), 101(Suppl.1), 5220-5227.
E. A. Erosheva. Partial Membership Models with Application to Disability Survey Data. In H. Bozdogan, ed., Statistical Data Mining and Knowledge Discovery, (2004) Chapman & Hall/CRC, 117-134.
E. A. Erosheva. Bayesian Estimation of the Grade of
Membership Model. Bayesian Statistics 7,
(J.M. Bernardo, M.J. Bayarri, J.O. Berger, A.P. Dawid, D. Heckerman, A.F.M. Smith and M. West, eds) (2003) Oxford, UK: Oxford University Press.
E. A. Erosheva, S. E. Fienberg, and B. J. Junker. Alternative Statistical Models and Representations for Large Sparse Multi-dimensional Contingency Tables, Annales de la Faculté des Sciences de l'Université de Toulouse Mathématiques (2002), 11.