STAT/BIOST 572, Spring 2014
Advanced Regression Methods
Instructions for Students
The list of papers for Stat/Biost 572 is given below, up to and including Spring 2012.
Instructions for Faculty
In 572, students study a methods paper in depth, writing a report on
the paper and its place in the statistical literature, and giving
several talks on its content. The papers are suggested by faculty, who
may (optionally) also advise students. As this course follows 570 and
571, the methods covered should be regressionbased, but this is
interpreted broadly.
A list of previous 572 papers is below. Strikethrough (i.e. strikethrough)
indicates that a paper was used, by the student named in parentheses;
these papers will not be available for use in 572 this year. Please
review the list, and do one of the following;
 If the two papers you listed are available, and you don't want to change them: Do nothing
 If you are not listed, or some of your papers were used, or you want to change papers: email the course instructor
Suggested papers
Listed alphabetically by faculty member
Bill Barlow
 Barlow WE. Robust variance estimation for the casecohort design. Biometrics. 1994 Dec;50(4):106472.
 Heagerty PJ, Zheng Y. Survival model predictive accuracy and ROC curves. Biometrics. 2005 Mar;61(1):92105.
Norm Breslow
 Breslow NE, Lumley T, Ballantyne CM, Chambless LE, Kulich M: Using the whole cohort in the analysis of casecohort data. Am J Epidemiol 169(11):1398405, 2009
 Breslow
NE, Lumley T, Ballantyne CM, Chambless LE, Kulich M: Improved
HorvitzThompson estimation of model parameters from twophase
stratified samples: applications in epidemiology. Statistics in Biosciences 1(1):3249, 2009
Elizabeth BrownBiometrics. 2003 Sep;59(3):52130 A Bayesian approach for joint modeling of cluster size and subunitspecific outcomes. Dunson DB, Chen Z, Harry J. (Rong Fu)Biometrics. 2000 Dec;56(4):100715. Bayesian estimators for conditional hazard functions. McKeague IW, Tighiouart M. (Stefan Sharkansky)
Sharon Browning
 Yang, J. et al. Common SNPs explain a large proportion of the heritability
for human height. NATURE GENETICS 42, 5659 (2010)
Zuk, O., Hechter, E., Sunyaev, S.R. & Lander, E.S. The mystery of missing
heritability: Genetic interactions create phantom heritability. Proceedings
of the National Academy of Sciences of the United States of America 109,
11938 (2012) (Elisa Sheng)
 Han L, Abney M (2011) "Identity by descent estimation with dense genomewide genotype data." Genetic Epidemiology 35: 557567.
Gary ChanQin J., Zhang B and Leung DHY (2009) Empirical likelihood in missing data problems. JASA 104 (488), 14921503 (Cheng Zheng) Copas (1983) Regression, prediction and shrinkage. JRSSB 45, 311354

Zhang, M., Tsiatis, A.A., and Davidian, M. (2008) Improving efficiency of inferences in randomized clinical trials using auxiliary covariates. Biometrics, 64, 707715 (Rui Zhang)
 Koenker R. (2004) Quantile regression for longitudinal data. Journal of Multivariate Analysis 91(1): p.7489.
 Chan KCG, Chen YQ and Di C (2012). Proportional Mean Residual Life Model
for Censored Lengthbiased Data of Prevalent Cohort. Biometrika 99 (4):
9951000.
 Chan KCG (2013). Nuisance parameter elimination for proportional likelihood
ratio models with nonignorable missingness and random truncation.
Biometrika 100 (1): 269276.

Chan, KCG (2013). Survival analysis without survival data: connecting
lengthbiased and casecontrol data. Biometrika, in press.
Adrian Dobra Dobra, A. (2009). Variable selection and dependency networks for
genomewide data Biostatistics, 10, 621639
Hans, C., Dobra, A. and West, M. (2007). Shotgun stochastic search for 'large p' regression. Journal of the American Statistical Association,
102, 507516. (Kirk Le)
Mathias Drton
 B"uhlmann, Peter. Statistical significance in highdimensional linear models, to appear in Bernoulli, link to paper
 Chen, Jiahua; Chen, Zehua. Extended Bayesian information criteria for model selection with large model spaces. Biometrika 95 (2008), no. 3, 759771.
 Ravikumar, Pradeep; Lafferty, John; Liu, Han; Wasserman, Larry. Sparse additive models. J. R. Stat. Soc. Ser. B Stat. Methodol. 71 (2009), no. 5, 10091030.
Scott Emerson
 Emerson SS, Fleming TR: Parameter estimation following group sequential hypothesis testing.
Biometrika 77:875892, 1990.
Alonzo, T.A. and Pepe, M.S. (2002). Distributionfree ROC analysis using binary regression techniques. Biostatistics 3, 421432. (Andrew Spieker)
 Dodd LE, Pepe MS. Partial AUC estimation and regression. Biometrics
2003; 59:614623.
 Rudser KD, LeBlanc ML, Emerson SS. Estimation for arbitrary functionals of survival. Statistics in Medicine 2012 31:17221737.
 Levin GP, Emerson SC, Emerson SS. An evaluation of inferential procedures for adaptive clinical trial designs with prespecified rules for modifying the sample size. Biometrics (in press)
Mary Emond
 Pan, W and Chappell R. Estimation in the Cox PH Model with LeftTruncated and IntervalCensored Data. Biometrics 58, 6470. March 2002
 Sun J and Wei LJ. Regression analysis of panel count data with coveriatedependent observation and censoring times. JRSSB 62:292302. 2000
Elana Erosheva
 I. Moustaki and M. Knott. (2000) "Generalized latent trait models." Psychometrika 65(3): 391411.
 K. Nowicki and T.A.B. Snijders (2001) "Estimation and Prediction for Stochastic Blockstructures." Journal of the American Statistical Association, 96(455):10771087.
 T. A.B. Snijders, P. E. Pattison, G. L. Robins, and M.S. Handcock. (2006) "New specifications for exponential random graph models" Sociological Methodology 36(1): 99153.
 E. M. Airoldi, D. M. Blei, S.E. Fienberg, and E.P. Xing (2008) "Mixed Membership Stochastic Blockmodels" Journal of Machine Learning Research 9:19812014.
 C. E.G. Steglich, T. A.B. Snijders, and M.Pearson (2010). Dynamic Networks and Behavior: Separating Selection from Influence. Sociological Methodology, 40, 329392.
 B. C. Heggeseth and N.P. Jewell (2011) "The impact of covariance misspecification in multivariate Gaussian mixtures on estimation and inference: an application to longitudinal modeling." Statitsics in Medicine 32:27902803.
 D. Telesca, E. A. Erosheva, D. Kreager, and R. Matsueda. ``Modeling Criminal Careers as Departures from a Unimodal AgeCrime Curve: The Case of Marijuana Use,'' Journal of the American Statistical Association (2012), 107(500):14271440
 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
Peter Gilbert

Prentice RL, Kalbfleisch JD, Peterson AV, Jr, Flournov N, Farewell VT, Breslow NE. The analysis of failure times in
the presence of competing risks.
Biometrics 1978;34:541554.(Yingying Zhuang)
Sun Y, Gilbert PB, McKeague IW. Proportional hazards models with continuous marks. Ann Stat. 2009;37(1):394426.(Jason Shao)
 Jemiai Y, Rotnitzky A, Shepherd BE, Gilbert PB. Semiparametric estimation of treatment effects given baseline
covariates on an outcome measured after a postrandomization event occurs. Journal of the Royal Statistical Society
Series BStatistical Methodology. 2007;69:879901.
Betz Halloran
 Chan, ISF, Shu, H, Matthews, C et al. 2002; Use of statistical
models for evaluating antibody response as a correlate of protection
against varicella. Statistics in Medicine 21:34113430
 Gilks, WR , Wang, CC, Yvonnet B, and Coursaget, J. Randomeffects models for longitudinal data using Gibbs sampling Biometrics 49:441454, 1993
Patrick HeagertyDonnelly CA, Laird NM, Ware JH (1995). Prediction and creation of smooth curves for temporally correlated longitudinal data. JASA 90: 984989 (Shirley You)
Heagerty
PJ, Pepe MS (1999). Semiparametric estimation of regression quantiles
with application to standardizing weight for height and age in US
children. JRSSC 48:533551 (Cheng Zheng)
 Qian M, Murphy SA (2011). Performance guarantees for individualized treatment rules. Annals of Statistics , 39(2): 11801210.
Peter HoffWhite (1982) Maximum likelihood estimation of misspecified models
Econometrica Vol. 50, No. 1 (Jan., 1982), pp. 125 (James Harmon)
 Box and Cox (1964) An Analysis of Transformations Journal of the Royal Statistical Society. Series B, Vol. 26, No. 2, pp. 211252
and
Bickel and Docksum (1981) An Analysis of Transformations Revisited Journal of the American Statistical Association, Vol. 76, No. 374 pp. 296311 and Box and Cox (1982) An Analysis of Transformations Revisited, Rebutted
Journal of the American Statistical Association, Vol. 77, No. 377 pp. 209210
George and McCulloch (1993) Variable selection via Gibbs sampling
Journal of the American Statistical Association, Vol. 88, No. 423 pp. 881889 (Alex Volfovsky)
Hoff PD: Extending the rank likelihood for semiparametric copula estimation. Ann. Appl. Stat., 1(1):265–283, 2007 (David Gerard)
 Owen AB: Empirical likelihood ratio confidence intervals for a single functional.
Biometrika 75 (1988), no. 2, 237–249.
Jim HughesHughes JP: Mixed effects models with censored data with application to HIV RNA levels. Biometrics, 55:625629, 1999 (Leigh Fisher)
 Moore
KL and van der Lann MJ: Covariate adjustment in randomized trials with
binary outcomes: Targeted maximum likelihood estimation. Statistics in Medicine, 28:39  64, 2009
Lurdes InoueLawless, J.F. (1987). Regression methods for Poisson process data. JASA, 82 (399), 808815 (Mark Wheldon) Kalbfleisch, J.D and Lawless, J.F. (1985). The analysis of panel data under a Markov assumption. JASA, 80(392), 863871 (Wenying Zheng)
Dror HA, Steinberg DM (2008). Sequential Experimental Designs for Generalized Linear Models. JASA 103:481, 288298. (Bob Salim)
 Dixon DO, Simon R (1991). Bayesian subset analysis.
Biometrics 47(3): 871881.
Katie KerrSmyth, Gordon K. (2004) Linear Models and
Empirical Bayes Methods for Assessing Differential Expression in
Microarray Experiments. Statistical Applications in Genetics and Molecular Biology: Vol. 3 : Iss. 1, Article 3(Aaron Baraff)

Cui X, Hwang JT, Qiu J, Blades
NJ, Churchill GA (2005)
Improved statistical tests for differential gene expression by
shrinking variance components estimates.
Biostatistics. 2005 Jan;6(1):5975
 Pepe, Fan, Seymour (2013) Estimating the Receiver Operating Characteristic Curve in Studies that Match Controls to Cases on Covariates,
Academic Radiology, Volume 20, 863873, 2013
Michael LeBlancLogic Regression. Ingo Ruczinski, Charles Kooperberg and Michael LeBlanc Journal of Computational and Graphical Statistics Vol. 12, No. 3 (Sep., 2003), pp. 475511 Extreme regression. Michael LeBlanc, James Moon and Charles Kooperberg Biostatistics 2006 7(1):7184
(Jason Liang)
Brian Leroux
Leroux BG, Mancl LA, DeRouen TA. Group sequential testing
in clinical trials with longitudinal data on multiple outcome variables.
Statist Meth Med Res 14:5019, 2005
(Clara DomiguezIslas) Stoner JA, Leroux BG: Analysis of clustered data: A combined estimating equations approach. Biometrika 89(3):567578, 2002
Thomas Lumley
 The Weighted Residual Technique for Estimating the Variance of the
General Regression Estimator of the Finite Population Total; CarlErik
Sarndal, Bengt Swensson, Jan H. Wretman. Biometrika, Vol. 76, No. 3 (Sep., 1989), pp. 527537
 Weighting for Unequal Selection Probabilities in Multilevel
Models; D. Pfeffermann, C. J. Skinner, D. J. Holmes, H. Goldstein, J.
Rasbash. Journal of the Royal Statistical Society. Series B, Vol. 60, No. 1 (1998), pp. 2340
Lipsitz et al (1994) Performance of Generalized Estimating Equations in Practical Situations Biometrics 50(1) 270278 (Chris JordanSquire)
Robyn McClelland
 Lee WC (2011): Bounding the bias of unmeasured factors with confounding
and effectmodifying
potentials. Stat in Med 30:10071017.
 Nguyen T, Jiang J.(2011) Restricted fence method for covariate selection
in longitudinal data analysis; Biostatistics. 13(2): 303314.
 Sjolander A, Vansteelandt S. (2011) Doubly robust estimation of
attributable fractions. Biostatistics. 12(1): 112121.
Tyler McCormick

Holmes, Chris C., and Leonhard Held. "Bayesian auxiliary variable
models for binary and multinomial regression." Bayesian Analysis 1.1
(2006): 145168.(Rebecca Ferrell)
 Clyde, Merlise, Giovanni Parmigiani, and Brani Vidakovic. "Multiple
shrinkage and subset selection in wavelets." Biometrika 85.2 (1998):
391401.
 Ho, Qirong, Ankur P. Parikh, and Eric P. Xing. "A multiscale
community blockmodel for network exploration." Journal of the American
Statistical Association 107.499 (2012): 916934.
 Abbring, Jaap H., and Gerard J. Van Den Berg. "The unobserved
heterogeneity distribution in duration analysis." Biometrika 94.1
(2007): 8799.
 Erven, Tim van, Peter Grünwald, and Steven de Rooij. "Catching up
faster by switching sooner: a predictive approach to adaptive
estimation with an application to the AICBIC dilemma." Journal of the
Royal Statistical Society: Series B (Statistical Methodology) 74.3
(2012): 361417.
Zhang, XianXing, Lawrence Carin, and David B. Dunson.
"Treestructured infinite sparse factor model." Proceedings of the
28th International Conference on Machine Learning (ICML11). 2011.(Ted Westling)
Barbara McKnightSong and Nicolae (2009) Restricted Parameter Space Models for Testing GeneGene Interaction. Genetic Epidemiology 33: 386 393. (Shizen Wang)
Madsen BE and Browning SR. A Groupwise Association Test for Rare Mutations Using a
Weighted Sum Statistic PLoS Genet 5(2): e1000384 (Phillip Keung)
Diana MigliorettiHeagerty PJ, Kurland BF: Misspecified maximum likelihood estimates and generalized linear mixed models. Biometrika 88: 973985, 2001 (Leila Zelnick)
Vladimir MininNeal R, Regression and Classification Using Gaussian Process Priors Bayesian Statistics 6 (Jon Fintzi)
Hsu JSJ and Leonard T Hierarchical Bayesian Semiparametric Procedures for Logistic Regression Biometrika Vol. 84, No. 1, pp. 8593 (Amanda Allen)
Martina Morris
 Goodreau S Kitts J and Morris M. Birds of a Feather, or Friend of a
Friend? Using Exponential Random Graph Models Investigate Adolescent
Social Networks Demography 2009 46(1)
Don Percival
 Peter Hall; Berwin A. Turlach; Interpolation Methods for Nonlinear Wavelet Regression with Irregularly Spaced Design, The Annals of Statistics
Vol. 25, No. 5, Oct., 1997
pp. 19121925
 HeeSeok Oh, Douglas W. Nychka, and Thomas C. M. Lee
The Role of Pseudo Data for Robust Smoothing with Application to Wavelet Regression, Biometrika, Vol. 94, No. 4, 2007, pp. 893904
S. J. Koopman and K.M. Lee (2009) Seasonality with Trend and Cycle Interactions in Unobserved Components Models, Journal of the Royal Statistical Society Series C Volume 58, Pages 427448 (Stefan Sharkansky)
Michael PerlmanM. Drton, M. D. Perlman (2004). Model selection for Gaussian
concentration graphs. Biometrika 91:3 591602
(Theresa Smith)
M. Drton, M. D. Perlman (2008). A SINful Approach to Gaussian
graphical model selection. Journal of Statistical Planning and
Inference 138, 11791200(Adam Gustafson)
Li Qin
 Variable Selection via Nonconcave Penalized Likelihood and its
Oracle Properties, Jianqing Fan and Runze Li, Journal of the American
Statistical Association 2001, Vol. 96, No. 456
 Zou, H. and Li, R. (2008). Onestep sparse estimates in
nonconcave penalized likelihood models (with discussion). Annals of
Statistics, 36, 15091566.
Adrian Raftery
 Sloughter, J.M., Raftery, A.E. and Gneiting, T. (2007). Probabilistic
Quantitative Precipitation Forecasting Using Bayesian Model Averaging.
Monthly Weather Review, 135, 32093220. (A similar paper is about to come out in JASA)
Fraley, C. and Raftery, A.E. (2007). Bayesian Regularization for Normal
Mixture Estimation and ModelBased Clustering. Journal of
Classification, 24, 155181 (Ricky Chielecki)
Taylor J and Verbyla A (2008) Joint modelling of location and scale parameters of the t distribution Statistical Modelling July 4(2) 91112 with Langa KL, Little RA and Taylor JMG (1989) Robust Statistical Modeling Using the t Distribution JASA 84(408) 881896 (Nevena Lalic)
Ken Rice
Microarrays, Empirical Bayes and the TwoGroups Model. Bradley Efron. Statist. Sci. Volume 23, Number 1 (2008), 122. (Yates Coley)
Control of the Mean Number of False Discoveries, Bonferroni and Stability of Multiple Testing. Gordon et al. Annals of Applied Statistics 2007, Vol. 1, No. 1, 179–190 (Caitlin McHugh)
Brown PJ, Fearn T and Vannucci M (1999) The Choice of Variables
in Multivariate Regression: A NonConjugate Bayesian Decision Theory
Approach. Biometrika 86(3) 635648 (Rui Zhang)
 Zhang, M., Tsiatis, A.A., and Davidian, M. (2008) Improving efficiency of inferences in randomized clinical trials using auxiliary covariates. Biometrics, 64, 707715
Spiegelhalter DJ, Best NG, Carlin BP and Van der Linde A, "Bayesian Measures of Model Complexity and Fit (with Discussion)", Journal of the Royal Statistical Society, Series B, 2002 64(4):583616.(Lina Lin)
 Gelman, A., Meng, X.L. and Stern, H. (1996). Posterior Predictive Assessment of Model Fitness via Realized Discrepancies. Statistica Sinica 6, 733807 (with discussion)
Barbra Richardson
 Vansteelandt, S., Goetghebeur, E. and Verstraeten, T. (2000)
Regression models for disease prevalence with diagnostic tests on pools
of serum samples Biometrics, 56, 11261133
Beale, E. M. L. and Little, R. J. A. (1975) Missing values in multivariate analysis. Journal of the Royal Statistical Society, Series B, 37, 129145 (Roddy Theobald)
Thomas Richardson
M.H. Maathuis, M. Kalisch, P. Buehlmann (2009), Estimating
highdimensional intervention effects from observational data. Annals
of Statistics 37, 31333164 (Chris Glazner) Hirano K, Imbens G, Rubin D, Zhou X (2000) Assessing the Effect of an Influenza Vaccine in an Encouragement
Design with Covariates, Biostatistics 1, 6988

Richardson, T., Robins, J.M. and Evans, R.J. (2011) Transparent
parametrizations of models for potential outcomes (with discussion), Valencia 9, pp 569610
(WenWei Loh)
Carolyn Rutter
 Rutter CM, Miglioretti DL, Savarino JE. Bayesian calibration of microsimulation models, JASA 2009; 104(488):13381350
 Rutter CM, Gatsonis CA. A hierarchical regression approach to metaanalysis of diagnostic test accuracy evaluations, Statistics in Medicine, 2001; 20(19):28652884
 Rutter CM, Simon G. A Bayesian method for relating crosssectional and longitudinal measures, Journal of the Royal Statistical Society, Series C: Applied Statistics, 2004; 53(2):341353.
 Zheng W, Rutter CM. Estimated Mean Sojourn Time Associated with Hemoccult SENSA, Cancer Epidemiology Biomarkers and Prevention, 2012; 21(10):172230.
Ali Shojaie
 Yuan M, Lin Y: Model selection and estimation in regression with grouped variables, JRSSB 2006; 68(1): 4967.
 Kalisch M, Buhlmann P: Estimating higdimensional directed acyclic graphs with the PCalgorithm. Journal of Machine Learning Research (2007); 613636.
Lianne Sheppard
Pacoriak, CJ. The Importance of Scale for
SpatialConfounding Bias and Precision
of Spatial Regression Estimators. Statistical Science
2010, Vol. 25, No. 1, 107125(Colin Sowder)
 Neuhaus JM, McCulloch CE, Separating between and
withincluster covariate effects by using conditional and
partitioning methods. JRSSB 2006, 68, 859872.
 Hodges JS, Reich BJ. Adding spatiallycorrelated errors can
mess up the fixed effect you love. American Statistician, 2010,
64, 325334.
Galen ShorackEfron B (1987) Better bootstrap confidence intervals Journal of the American Statistical Association, Vol. 82, No. 397 pp. 171185(Greg Imholte)
 Hampel (1974) The influence curve and its role in robust estimation Journal of the American Statistical Association, Vol. 69, No. 346 pp. 383393
Adam Szpiro
A. Gryparis, C. J. Paciorek, A. Zeka, J. Schwartz, and B. A.
Coull. Measurement error caused by spatial misalignment in environmental
epidemiology. Biostatistics, 10(2):258–274, 2009 (Laina Mercer)
Szpiro AA, Sheppard L, and Lumley T, Efficient measurement error correction with spatially misaligned data, Biostatistics, in press (Silas Bergen)
 Hodges J and Reich. Adding SpatiallyCorrelated Errors Can Mess Up
the Fixed Effect You Love The American Statistician. November 1, 2010, 64(4): 325334
Szpiro AA, Rice KM, and Lumley T. Modelrobust regression and a Bayesian 'sandwich' estimator. Annals of Applied Statistics, Vol 4(4), 2010 (David Benkeser)
 Bayesian effect estimation accounting for adjustment uncertainty. Wang C, Parmigiani G, Dominici F. (2012)
 Matern CrossCovariance Functions for Multivariate Random Fields. Tilmann Gneiting, William Kleiber, and Martin Schlather (2010)
 Bergen S, Sheppard L, Sampson PD, Kim SY, Richards M, Vedal S, Kaufman JD, and Szpiro AA. A national prediction model for components of PM2.5 and measurement error corrected health effect inference. Environmental Health Perspectives, Vol 121, 10171025, 2013.
 Szpiro AA and Paciorek CJ. Measurement error in twostage analyses, with application to air pollution epidemiology. Environmetrics, Vol 24, 501517, 2013.
 Szpiro AA, Sheppard L, Adar SD, and Kaufman JD. Estimating acute air pollution health effects from cohort study data. Biometrics, Vol 70, 164174, 2014. DOI: 10.1111/biom.12125
MaryLou Thompson
De la CruzMesía R, Quintana FA, Marshall G. Modelbased clustering for longitudinal data. Computational Statistics & Data
Analysis 2008; 52 :1441 – 1457. (Amrit Dhar)
 Marschner IC, Gillett AC. Relative risk regression: reliable and flexible methods for logbinomial models. Biostatistics 2012;
13:17992
Timothy Thornton
 Kang, H. M., Sul, J. H., Service, S. K., Zaitlen, N. A., Kong, S.Y., Freimer, N. B., Sabatti, C. Eskin, E. (2010) Variance component model to account for sample structure in genomewide association studies. Nat Genet 42, 348354.
 Thornton, T., McPeek, M.S. (2007) Casecontrol association testing with related individuals: a more powerful quasilikelihood score test. Am J Hum Genet 81, 321337.
Jon Wakefield
 Prentice, R. L. and Sheppard, L. (1995). Aggregate data studies of disease risk factors. Biometrika 82, 113125.
Plummer, M. (2008). Penalized loss functions for Bayesian model comparison. Biostatistics, 9, 523539. (Josh Keller)
Pei Wang Efron, Bradley; Hastie, Trevor; Johnstone, Iain and Tibshirani, Robert (2004). Least Angle Regression Annals of Statistics 32 (2): pp. 407–499
Meinshausen, N. and Bühlmann, P. (2006). Highdimensional graphs and variable selection with the Lasso. Annals of Statistics 34, 14361462.(Ibraheem Mohammed)
Bruce Weir
 Hill, W.G. and B.S. Weir. 2011. Variation in actual relationship as a consequence of Mendelian sampling and linkage. Genetics Research 93:4774.
 Weir, B.S. 2013. Interpreting wholegenome marker data. Statistics in Biosciences 5:316329.
Jon Wellner
A list of 10 papers is available here
Daniela Witten
Zou and Hastie (2005) Regularization and variable selection via the elastic net. JRSSB 67(2) 301320 (Alison Kosel)
Mazumder, Hastie, and Tibshirani (2010) Spectral regularization algorithms for learning large incomplete matrices. Journal of Machine Learning Research 11 22872322 (Amol Kapila)
Friedman, Hastie and Tibshirani (2008) Sparse inverse covariance estimation with the graphical lasso Biostatistics 9(3) 432441 with Yuan and Lin, Model selection and estimation in the Gaussian graphical model Biometrika (2007) 94(1):1935 (Arie Voorman)
Bien J, Tibshirani R: Sparse estimation of a
covariance matrix. Biometrika (2011); 98(4): 807820. (Sen Zhao)
 Tibshirani R, Saunders M, Rosset S, Zhu J, Knight K: Sparsity and smoothness via the fused lasso.
Journal of the Royal Statistical Society Series B (2004); 67(1): 91108.
Rothman AJ, Bickel PJ, Levina E, Zhu J: Sparse permutation invariant covariance estimation. Electron.
J. Statist. (2008); Volume 2, 494515. (David Prince)
P.D. Hoff. Separable covariance arrays via the Tucker product, with applications to multivariate relational data. Bayesian Analysis, 6:179 (Kean Ming Tan)
H Zhou, L Li, and H Zhu. (2013) Tensor regression with applications in neuroimaging data analysis, Journal of American Statistical Association, accepted. link to paper (Jen Kirk)
Richard Lockhart, Jonathan Taylor, Ryan Tibshirani and Robert Tibshirani. A significance test for the lasso (submitted) link to paper (Ashley Peterson)
David Yanez Pepe MS, Anderson GL (1994) A cautionary note
on inference for marginal regression models with longitudinal data and
general correlated response data. Communications in Statistics and Simulation, 23, 939–51 (Jing Fan)
 Crouchley R, Davies RB (1999). A comparison of population average
and random effects models for the analysis of longitudinal count data
with baseline information. Journal of the Royal Statistical Society, Series A, 162, 331–47  together with
 Thomas Lumley, Margaret S. Pepe, Patrick J. Heagerty, Robert
Crouchley, Richard Davies. Analysis and Interpretation of Disease
Clusters and Ecological Studies (2001), Journal of the Royal Statistical Society. Series A, Vol. 164, No. 1, pp. 209212.
Yingye Zheng
 ModelChecking Techniques Based on Cumulative Residuals, D. Y. Lin, L. J. Wei and Z. Ying, Biometrics, Vol. 58, No. 1 pp. 112
 Logistic disease incidence models and casecontrol studies, R. L. Prentice and R. Pyke, Biometrika 1979 66(3):403411
Andrew Zhou Rodenberg CA, Zhou XH. ROC curve estimation when covariates affect the verification process. Biometrics 2000; 56: 125662.
Zhou
XH, Lin H, and Eric Johnson. Nonparametric heteroscedastic
transformation regression models for skewed data with an application to
health care costs. Journal of Royal Statistical Society Series B 2008; 70: 10291047(Scott Coggeshall)
