Mather KJ, Pan Q, Knowler WC, Funahashi T, Bray GA, Arakaki R, Falkner B, Sharma K, and Goldstein BJ. Treatment-induced changes in plasma adiponectin do not affect urinary albumin excretion in the Diabetes Prevention Program cohort. Plos One 2015, 10(8): e0136853.

Papandonatos G.D., Pan Q., Pajewski N., Delahanty L.M., Peter I., Erar B., Ahmad S., Harden M., Chen L., Fontanillas P., Wagenknecht L., Kahn S., Wing R., Jablonski K., Huggins G., Knowler W., Florez J., McCaffery J., Franks P. Genetic predisposition to weight loss & regain with lifestyle intervention: Analyses from the Diabetes Prevention Program & the Look AHEAD randomized controlled trials. Diabetes Care 2015, 64:4312-4321.

Delahanty, L.M., Pan, Q., Jablonski, K.A., Aroda, V.R., Watson, K., Bray, G.A., Kahn, S.E., Florez, J.C., Perreault, L. and Franks, P.W. Effects of weight loss, weight cycling and weight loss maintenance on diabetes incidence and cardiometabolic traits in the diabetes prevention program. Diabetes Care 2014 Oct, 37(10): 2738-45.

Zhao, Y., Pan, Q. and Du, C. Logistic regression augmented community detection (Biometrics).

Cheung, L., Pan, Q., Hyun, N., Schiffman, M., Fetterman, B., Castle, P.E. and Hormudz, K. Mixture models for left-censored and irregularly interval-censored data: Application to a cancer screen cohort assembled from electronic health records. (Statistics in Medicine)

Hyun, N., Cheung, L., Pan, Q., Schiffman, M. and Hormuzd, K.  Weakly-parametric weighted mixture models for left or interval-censored data with application to electronic health records (Annals of Applied Statistics)

Gastwirth JG, Miao W, Pan Q. Statistical issues arising in the Kerner v. Denver, a class action disparate impact case (Law, Probability & Risk)

Pan Y, Yan C, Hu Y, Wan Q, Pan Q, Torcivia  J, Mazumder R. Analysis of the distribution of SNV in microenvironment of protein functional sites reveals different and significant distributional bias for germline and somatic mutations (Scientific Reports - Nature)

Pan, Q. and Zhao, Y. Integrative weighted group lasso and generalized local quadratic approximation. (Computational Statistics & Data Analysis)

Gastwirth, J.L., Xu, W. and Pan, Q. Statistical methods for evaluating minority under-representation on juries and venires: Analysis of the conflicting inferences drawn from the same data in People v. Bryant and Ambrose v. Booker. Law, Probability & Risk 2015, 14(4): 279-304 

Gastwirth, J.L. Xu, W. and Pan. Q. Did the Michigan Supreme Court Appreciate the Implications of Adopting the “Disparity of the Risk” Measure of Minority Representation in Jury Pools in People v. Bryant? Statistics and Public Policy 2014, 1, 129-132.

Pan, Q. Multiple testing methods in clinical trials and genomic studies. Frontiers in Public Health 2013, 1(63): 1-8. doi: 10.3389/fpubh.2013.00063

Xu, W., Pan, Q. and Gastwirth, J.L. Proportional hazards models with frailty for negatively correlated processes. Computational Statistics & Data Analysis 2014, 70: 295-307 .

Xu, W., Pan, Q. and Gastwirth, J.L. Adaptive procedures for nested processes: Application to equal employment. Statistics & Its Inference 2013, 6(4): 1-13 

Pan, Q. and Schaubel, D.E.  Proportional hazards regression in the presence of missing study eligibility information. Lifetime Data Analysis, DOI: 10.1007/s10985-013-9273-5.

Pan, Q. and Gastwirth, J.L. Estimating restricted mean job tenures in semi-competing risk data compensating victims of discrimination. Annals of Applied Statistics, 2013, 7(3): 1474-1496.

Pan, Q. Case Comment: Adams v. Perrigo and the appropriate criterion for bioequivalence in patent infringement cases. Law, Probability & Risk 2013, 12(2): 147-153 

Pan, Q. and Gastwirth, J.L. The appropriateness of survival analysis for determining lost pay in discrimination cases: application of the ‘Lost Chance’ doctrine to Alexander v. Milwaukee.  Law, Probability & Risk  2013, 12(1): 13-35

Pan, Q. and Grace, Y.Y.  An estimation method of marginal treatment effects on correlated longitudinal and survival outcomes. Statistics and Its Inference 2011, 4(4): 499-509. 

Gastwirth, J.L. and Pan, Q. Statistical measures and methods for assessing the representativeness of juries: a reanalysis of the data in Berghuis v. Smith. Law, Probability & Risk 2011, 10(1): 17-57 

Pan, Q. and Schaubel, D.E.  Evaluating bias correction in weighted proportional hazards regression.  Lifetime Data Analysis 2009, 15(1): 120-146. 

Pan, Q. and Schaubel, D.E.  Flexible estimation of differences in treatment-specific recurrent event means in the presence of a terminating event.  Biometrics 2009, 65(3): 753-761.

Pan, Q. and Gastwirth, J.L. Issues in the use of survival analysis to estimate damages in equal employment cases. Law, Probability & Risk 2009, 8(1): 1-24 

Gastwirth, J.L. and Pan, Q. Diaz v. Eagle Produce Ltd. Partnership: the potential for and limitations of formal statistical analysis to assist courts when drawing inferences from a relatively small data set. Jurimetrics 2009, 49(4): 439-466. 

Sinclair, M.D. and Pan, Q. Using the Peters-Belson Method in EEO personnel evaluations (with Comments). Law, Probability & Risk 2009, 8(2): 95-117 

Pan, Q. and Schaubel, D.E.  Weighted Cox regression with biased samples and empirically estimated selection probabilities. Canadian Journal of Statistics 2008, 36(1): 111-127. 

Marrero, D., Pan, Q., Barrett-Connor, E., de Groot, M., Zhang, P., Percy, C., Florez, H., Ackermann, R., Montez, M. and Rubin, R.R., Impact of diagnosis of diabetes on health-related quality of life among high risk individuals: the DPP outcome study. Quality of Life Research 2013, doi: 10.1007/s11136-013-0436-3 

Pan, Q., Delahanty, L.M., Jablonski, K.A., Knowler, W.C., Kahn, S.E., Florez, J.C. and Franks, P.W.  Variation at the melanocortin 4 receptor gene and response to weight-loss interventions in the diabetes prevention program. Obesity 2013, doi: 10.1002/oby.20459 

Pollin, T. I., Isakova, T.,  Jablonski, K.A., de Bakker, P.I.W., Taylor, A.,  McAteer, J.,  Pan, Q., Horton, E.S., Delahanty, L.M., Altshuler, D., Shuldiner, A.R., Goldberg, R.B., Florez, J.C. and Franks, P.W. Genetic modulation of lipid profiles following lifestyle modification or metformin treatment: the diabetes prevention program. PloS Genetics 2012, 8(8): e1002895

Florez, H., Pan, Q., Rubin, R., Ackermann, R.T., Marrero, D.G., Barrett-Connor, E., Delahanty, L., Kriska, A., Saudek, C.D., Goldberg, R.B. and Rubin, R.R. Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial. Journal of General Internal Medicine 2012, 27(12): 1594-1601 

Perreault, L., Pan, Q., Mather, K.J., Watson, K.E., Saudek, C., Hamman, R.F. and Kahn, S.E. Effect of regression from prediabetes to normal glucose regulation on long-term reduction in diabetes risk: results from the Diabetes Prevention Program Outcomes Study. Lancet 2012, 379(9833): 2243-2251 

Delahanty, L.M., Pan, Q., Jablonski, K.A., Watson, K.E., McCaffery, J.M., Shuldiner, A., Kahn, S.E., Knowler, W.C., Florez, J.C. and Franks, P.W. Genetic predictors of weight loss and weight regain after intensive lifestyle modification, metformin treatment or standard care in the diabetes prevention program. Diabetes Care 2012, 35(2): 363-366

Damle, S., Teal, C.B., Lenert, J.J., Marshall, E.C., Pan, Q. and Mcswain, A.P. Mastectomy and contralateral prophylactic mastectomy rates: an institutional review.  Annals of Surgical Oncology 2011, 18(5): 1356-1363 

Hirth, R.A., Pan, Q.,  Schaubel, D.E. and Merion, R.M. Efficient utilization of the Expanded Criteria Donor (ECD) deceased donor kidney pool: an analysis of the effect of labeling. American Journal of Transplantation 2010, 10(2): 304-309.

Hirth, R.A., Turenne, M.N., Wheeler, J.R.C., Pan, Q., Ma, Y. and Messana, J.M. Provider monitoring and pay-for-performance when multiple providers affect outcomes: an application to renal dialysis. Health Service Research 2009, 44(5): 1585-1602 

Turenne, M.N., Hirth, R.A., Pan, Q., Wolfe, R.A., Messana, J.M. and Wheeler, J.R.C. Using knowledge of multiple levels of variation in care to target performance incentives to providers. Medical Care 2008, 46(2): 120-126 

Hirth, R.A., Turenne, M.N., Wheeler, J.R.C., Pozniak, A.S., Tedeschi, P., Chuang, C.C., Pan, Q., Slish, K. and Messana, J.M. Case-mix adjustment for an expanded renal prospective payment system. Journal of the American Society of Nephrology 2007, 18(9): 2565-2574 

Wheeler, J.R., Messana, J.M., Turenne, M.N., Hirth, R.A., Pozniak, A.S., Pan, Q., Chuang, C.C., Slish, K., Tedeschi, P., Roys, E.C. and Wolfe, R.A. Understanding the basic case-mix adjustment for the composite rate. American Journal of Kidney Disease 2006, 47(4): 666-671 

Gastwirth, J.L. and Pan, Q.  Comments on “Qualifying the weight of evidence from a forensic fingerprint comparison: a new paradigm” by C. Neumann, I.W. Evett & J. Skerrett J. R. Statistic. Soc. A 2012, 175(2): 402-403.

Pan, Q. Entry “Standard Error of Estimate” in Encyclopedia of Research Design edited by Neil Salkind,  2010, SAGE publications Inc: 1424-1427.

Gastwirth, J.L. and Pan, Q.  Careful statistical reasoning can provide support for supreme court decision. AmStat News 2010, 397: 23-24.