Long Research Group

Selected Publications

2023

• Zhou, Z.,¹ Ataee Tarzanagh, D.,¹ Hou, B., Tong, B., Xu, J., Feng, Y., Long, Q.,² and Shen, L.² (2023) Fair Canonical Correlation Analysis. 2023 Conference on Neural Information Processing Systems (NeurIPS 2023), accepted. ¹Joint first authors. ²Joint senior authors.
• Zhang, Q., Chang, C., Long, Q. (2023) Robust knowledge-guided biclustering for multi-omics data. Briefings in Bioinformatics, in press.
• Getzen, E., Ungar, L., Mowery, D., Jiang, X. and Long, Q. (2023) Mining for equitable health: Assessing the impact of missing data in electronic health records. Journal of Biomedical Informatics, p.104269.
• Chen, S., Zheng, Q., Long, Q., Su, W. (2023) Minimax Estimation for Personalized Federated Learning: An Alternative between FedAvg and Local Training. Journal of Machine Learning Research, in press.
• Bu, Z., Wang, H., Dai, Z., and Long, Q. (2023) On the Convergence and Calibration of Deep Learning with Differential Privacy. Transactions on Machine Learning Research, in press.
• Jang, A., Chang, C., Manatunga, A., Taylor, A.T., and Long, Q. (2023) An Integrative Latent Class Model of Heterogeneous Data Modalities for Diagnosing Kidney Obstruction. Biostatistics, in press.
• Bao, J., Chang, C. Shen, L. and Long, Q.  (2023) Integrative Analysis of Multi-omics and Imaging Data with Incorporation of Biological Information via Structural Bayesian Factor Analysis. Briefings in Bioinformatics, 24(2):1-15.
• Oh, J., Chang, C., and Long, Q. (2023) Accounting for Technical Noise in Bayesian Graphical Models of Single-cell RNA Sequencing Data. Biostatistics, 24 (1), 161-176.
• Tan, A.L.M.¹, Getzen, E.J.¹, Hutch, M.R., Strasser, Z.H., Gutierrez-Sacristan, A., Le, T.T., Dagliati, A., Morris, M., Hanauer, D.A., Moal, B., Bonzel, C., Yuan, W., Chiudinelli, L., Das, P., Zhang, H.G., Aronow, B.J., Avillach, P.,  Brat, G.A., Cai, T., Hong, C., La Cava, W.G., Loh, N.H.W., Yuan Luo, Y., Murphy, S.N., Ngiam, K.Y., Omenn, G.S., Patel, L.P., Samayamuthu, M.J., Schriver, E.R., Abad, Z.S.H., Tan, B.W.L., Tan, B.W.Q., Visweswaran, S., Wang, X., Weber, G.M., Xia, Z., PhD; Verdy, G., The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Long, Q.², Mowery D.L.², and Holmes, J.² (2023) Informative Missingness: What can we learn from patterns in missing laboratory data in the electronic health record? Journal of Biomedical Informatics, 139:104306. ¹Joint first authors. ²Joint senior authors.
• Chen, K., Heng, S., Long, Q., and Zhang, B. (2022)  Testing Relaxed Randomization Assumptions and Quantifying Residual Confounding in Matched Observational Studies: A Clustering With Side-Information Approach. Journal of Computational and Graphical Statistics, 32(2):528-38.
• Chang, C., Bu, Z., and Long, Q. (2023) CEDAR: Communication Efficient Distributed Analysis for Regressions. Biometrics, in press.
• Ataee Tarzanagh, D., Hou, B., Tong, B.,  Long, Q.  and Shen, L. (2023) Fairness-Aware Class Imbalanced Learning on Multiple Subgroups.  39th Conference on Uncertainty in Artificial Intelligence (UAI 2023). 

2022

• Jin, C., Lee, B., Shen, L., and Long, Q. (2022) Integrating multi-omics summary data using a Mendelian randomization framework. Briefings in Bioinformatics, 23(6):1-13.  
• Zhang, Y. and Long, Q. (2022) Fairness-aware Missing Data Imputation. NeurIPS 2022 Workshop: Trustworthy and Socially Responsible Machine Learning. 
• Chang, C.,  Dai, Z., Oh, J., and Long, Q. (2022) Integrative Learning of Structured High-Dimensional Data from Multiple Datasets. Statistical Analysis and Data Mining, in press.
• Zhang, Q., Bu, Z., Chen, K., and Long, Q. (2022) Differentially Private Bayesian Neural Network on Accuracy, Privacy and Reliability. 2022 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), in press.
• Wang, M., and Long, Q. (2022) Addressing Common Misuses and Pitfalls of P-values in Biomedical Research. Cancer Research, 82(15): 2674–267.
• Getzen, E., Ruan, Y., Ungar, L., and Long, Q. (2022) Mining for Health: A Comparison of Word Embedding Methods for Analysis of EHRs Data. Precision Medicine: Methods and Applications (Springer), in press.
• Baik, J.Y.,  Kim, M.,  Bao, J.,  Long, Q. and Shen, L. (2022) Identifying Alzheimer’s Genes via Brain Transcriptome Mapping.   BMC Medical Genomics, 15(Suppl 2):116.
• Kim M, Min EJ, Liu K, Yan J, Saykin AJ, Moore JH, Long, Q. and Shen, L. (2022) Multi- task learning based structured sparse canonical correlation analysis for brain imaging genetics. Medical Image Analysis, 76:102297.

2021

• Zhang, Y. and Long, Q. (2021) Assessing Fairness in the Presence of Missing Data. Advances in Neural Information Processing Systems (NeurIPS 2021), 34, 16007-16019.
• Fang, C., He, H., Long, Q., and Su, W. (2021) Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training. Proceedings of the National Academy of Sciences (direct submission), 118(43):e2103091118.
• Parikh, R.B., Min, E.J., Wileyto, E.P., Riaz, F., Gross, C.P., Cohen, R.B., Hubbard, R.A.,* Long, Q.,* and Mamtani R.* (2021) Uptake and Effectiveness of Checkpoint Inhibitor Therapy among Trial-Ineligible Patients with Advanced Solid Malignancies. JAMA Oncology, 7(12):1843-1850. *equal contribution
• Holmes, J., Beinlich, J. Boland, M.R., Bowles, K.H., Chen, Y., Cook, T.S., Demiris, G., Draugelis, M., Fluharty, L., Gabriel, P.E., Grundmeier, R., Hanson, C.W., Herman, D.S., Himes, B.E., Hubbard, R.A., Kahn, C.E., Kim, D., Koppel, R., Long, Q., Mirkovic, N., Morris, J.S., Mowery, D.L., Ritchie, M.D., Urbanowicz, R., and Moore, J. (2021) Why is the Electronic Health Record So Challenging for Research and Clinical Care?  Methods of Information in Medicine, 60(1-02):32-48.
• Zhang, Y., and Long, Q. (2021) Fairness in Missing Data Imputation. ICML 2021 Workshop: Socially Responsible Machine Learning.
• Jang, J.H., Manatunga, A., Chang, C. and Long, Q. (2021) A Bayesian Multiple Imputation Approach to Bivariate Functional Data with Missing Components. Statistics in Medicine, 40(22):4772-4793.
• Bu, Z., Wang, H., Long, Q., and Su, W. (2021) On the Convergence of Deep Learning with Differential Privacy. ICML 2021 Workshop: Theory and Practice of Differential Privacy.
• Zhang, Q., Bu, Z., Chen, K., and Long, Q. (2021) Differentially Private Bayesian Neural Network. ICML 2021 Workshop: Theory and Practice of Differential Privacy.
• Bu, Z., Dai, Z., Zhang, Y., and Long, Q. (2021) MISNN: Multiple Imputation via Semi- parametric Neural Networks. ICML 2021 Workshop: Subset Selection in Machine Learning: From Theory to Applications.
• Chen, K., and Long, Q. Distributed Gaussian Differential Privacy Via Shuffling. ICLR 2021 Workshop: Distributed and Private Machine Learning (DPML).
• Zheng, Q., Chen, S., Long, Q. and Su, W. (2021) Federated f-Differential Privacy. The 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021), 2251-2259.
• Dai, Z., Bu, Z., and Long, Q. (2021) Multiple Imputation via Generative Adversarial Network for High-dimensional Blockwise Missing Value Problems. 20th IEEE International Conference on Machine Learning and Applications (ICMLA 2021), 791-798, doi: 10.1109/ICMLA52953.2021.00131.

2020

• Chang, C., Jang, A., Manatunga, A., Taylor, A.T., and Long, Q. (2020) A Bayesian Latent Class Model to Predict Kidney Obstruction Based on Renography and Expert Ratings in the Absence of Gold Standard. Journal of the American Statistical Association, 115(532): 1645-1663.
• Chang, C., Deng, Y., Jiang, X. and Long, Q. (2020) Multiple Imputation for Analysis of Incomplete Data in Distributed Health Data Networks. Nature Communications, 11(1):5467.
• Zheng, Q., Dong, J., Long, Q., and Su, W. (2020) Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion. Proceedings of the 37th International Conference on Machine Learning (ICML 2020), 119:11420-11435.
• Bu, Z., Dong, J., Long, Q., and Su, W. (2020) Deep Learning with Gaussian Differential Privacy. Harvard Data Science Review, 2(3):1-48.
• Deng, Y., Jiang, X., and Long, Q. (2020) Privacy-Preserving Methods for Vertically Partitioned Incomplete Data. AMIA Annu Symp Proc. 2020:348-357.
• Eng, Y., Yao, X., Liu, K., Risacher, S.L., Nho, K., Saykin, A.J., Long, Q., Zhao, Y., and Shen, L. (2020) Polygenic mediation analysis of Alzheimer's disease implicated intermediate amyloid imaging phenotypes. AMIA Annu Symp Proc. 2020:422-431.
• Chang, C., Oh, J., and Long, Q. (2020) GRIA: Graphical Regularization for Integrative Analysis. 2020 SIAM International Conference on Data Mining (SDM 2020), 604-612.
• Li, Z., Chang, C., Kundu, S., and Long, Q. (2020) Bayesian Generalized Biclustering Analysis via Adaptive Structured Shrinkage. Biostatistics, 21(3):610-624.
• Leng, Q., Tarbe, M., Long, Q., and Wang, F. (2020) Pre-existing heterologous T cell immunity and neoantigen immunogenicity. Clinical & Translational Immunology,  9(3):e01111.

2019

• Zhao, Y., Chang, C., and Long, Q. Knowledge-guided statistical learning methods for analysis of high-dimensional -omics data in precision oncology. JCO Precision Oncology, 3:1-9, 2019.
• Chang, C., Min, E.J., Oh, J., and Long, Q. Knowledge-Guided Biclustering via Sparse Variational EM Algorithm. 2019 IEEE International Conference on Big Knowledge (IEEE ICBK 2019), 25-32, 2019.
• Li, Z., Roberts, K.E., Jiang, X., and Long, Q. Distributed Learning from Multiple EHR Databases: Contextual Embedding Models for Medical Events. Journal of Biomedical Informatics, 92:103138, 2019.
• Min, E.J., Safo, S.E., and Long, Q. “Penalized Co-Inertia Analysis with Application to Transcriptomic and Metabolomic Data.” Bioinformatics, 35(6):1018-1025, 2019.

2018

• Sun, W., Chang, C., Zhao, Y., and Long, Q. “Knowledge-guided Bayesian Support Vector Machine for High-Dimensional Data with Application to Genomic Data,”  2018 IEEE International Conference on Big Data (IEEE BigData 2018), pp. 1484-1493, 2018.
• Chang, C., Kundu, S., and Long, Q. “Scalable Bayesian Variable Selection for Structured High-dimensional Data,” Biometrics, 74(4):1372-1382, 2018.
• Min, E.J., Chang, C., and Long, Q. “Generalized Bayesian Factor Analysis for Integrative Clustering with Applications to Multi-Omics Data.”  The 5th IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA 2018), pp. 109-119, 2018.
• Safo, S.E., and Long, Q. “Sparse linear discriminant analysis in structured covariates space.” Statistical Analysis and Data Mining, in press, 2018.
• S. Safo, S. Li, and Q. Long, “Integrative analysis of transcriptomic and metabolomic data via sparse canonical correlation analysis with incorporation of biological information,” Biometrics, 74(1):300-312, 2018.
• Y. Zhao, J. Kang, and Q. Long, “Bayesian multiresolution variable selection for ultra-high dimensional neuroimaging data,” IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(2):537-550, 2018.
• Jang, J.H., Manatunga, A., Taylor, A.T., and Long, Q. “Overall Indices for Assessing Agreement Among Multiple Raters,” Statistics in Medicine, 37(28):4200-4215, 2018.
• M. Hammadah, I. Al Mheid, K. Wilmot, R. Ramadan, A. Alkhoder, M. Obideen, N. Abdelhadi, S. Fang, I. Ibeanu, P. Pimple, and others, “Association between high-sensitivity cardiac troponin levels and myocardial ischemia during mental stress and conventional stress,” JACC: Cardiovascular Imaging, 11(4):603-611, 2018.

2017

• Z. Li, S. E. Safo, and Q. Long, “Incorporating biological information in sparse principal component analysis with application to genomic data,” BMC Bioinformatics, 18(1):332, 2017.
• Y. J. Hu, A. F. Schmidt, F. Dudbridge, M. V. Holmes, J. M. Brophy, V. Tragante, Z. Li, P. Liao, R. McCubrey, B. Horne, A. Hingorani, F. Asselbergs, R. Patel, and Q. Long, “The impact of selection bias on estimation of subsequent event risk,” Circulation: Cardivascular Genetics, 10(5). pii: e001616, 2017.
• S. Clifton, C. Kang, J. Li, Q. Long, N. Shah, and D. Abrams, “Hybrid statistical and mechanistic mathematical model guides mobile health intervention for chronic pain,” Journal of Computational Biology, vol. 24, iss. 7, pp. 675-688, 2017.
• Y. Zhao and Q. Long, “Variable selection in the presence of missing data: imputation-based methods,” Wiley Interdisciplinary Reviews: Computational Statistics, 9(5), 2017.
• S. L. Jackson, S. Safo, L. R. Staimez, Q. Long, M. K. Rhee, S. A. Cunningham, D. E. Olson, A. M. Tomolo, U. Ramakrishnan, K. V. Narayan, and others, “Reduced cardiovascular disease incidence with a national lifestyle change program,” American Journal of Preventive Medicine, vol. 52, iss. 4, pp. 459-468, 2017.
• S. Jackson, S. Safo, L. Staimez, D. Olson, K. Narayan, Q. Long, J. Lipscomb, M. Rhee, P. Wilson, A. Tomolo, and others, “Glucose challenge test screening for prediabetes and early diabetes.,” Diabetic Medicine, vol. 34, iss. 5, pp. 716-724, 2017.
• M. Hammadah, I. Al Mheid, K. Wilmot, R. Ramadan, N. Abdulhadi, A. Alkhoder, M. Obideen, P. Pimple, O. Levantsevych, H. Kelli, and others, “Telomere shortening, regenerative capacity, and cardiovascular outcomes,” Circulation Research, vol. 120, iss. 7, pp. 1130-1138, 2017.
• K. L. Pellegrini, M. G. Sanda, D. Patil, Q. Long, M. Santiago-Jiménez, M. Takhar, N. Erho, K. Yousefi, E. Davicioni, E. A. Klein, and others, “Evaluation of a 24-gene signature for prognosis of metastatic events and prostate cancer-specific mortality,” BJU International, vol. 119, iss. 6, pp. 961-967, 2017.

2016

• Y. Zhao, M. Chung, B. A. Johnson, C. S. Moreno, and Q. Long, “Hierarchical feature selection incorporating known and novel biological information: identifying genomic features related to prostate cancer recurrence,” Journal of the American Statistical Association, vol. 111, iss. 516, pp. 1427-1439, 2016.
• M. Wang and Q. Long, “Addressing issues associated with evaluating prediction models for survival endpoints based on the concordance statistic,” Biometrics, vol. 3, iss. 72, pp. 897-906, 2016.
• Y. Deng, C. Chang, M. S. Ido, and Q. Long, “Multiple imputation for general missing data patterns in the presence of high-dimensional data,” Scientific Reports, vol. 6, iss. 21689, 2016.
• Q. Long, X. Zhang, Y. Zhao, B. A. Johnson, and R. M. Bostick, “Modeling clinical outcome using multiple correlated functional biomarkers: a bayesian approach,” Statistical Methods in Medical Research, vol. 25, iss. 2, pp. 520-537, 2016.
• Y. Zhao and Q. Long, “Multiple imputation in the presence of high-dimensional data,” Statistical Methods in Medical Research, vol. 25, iss. 5, pp. 2021-2035, 2016.
• C. Hsu, Y. He, Y. Li, Q. Long, and R. Friese, “Doubly robust multiple imputation using kernel-based techniques,” Biometrical journal, vol. 3, iss. 58, pp. 588-606, 2016.
• B. A. Johnson, Q. Long, Y. Huang, K. Chansky, M. Redman, and others, “Model selection and inference for censored lifetime medical expenditures,” Biometrics, vol. 72, iss. 3, pp. 731-741, 2016.
• M. A. Torres, X. Yang, S. Noreen, H. Chen, T. Han, S. Henry, D. Mister, F. Andic, Q. Long, and T. Liu, “The impact of axillary lymph node surgery on breast skin thickening during and after radiation therapy for breast cancer,” International journal of radiation oncology* biology* physics, vol. 95, iss. 2, pp. 590-596, 2016.
• P. S. Mishra-Kalyani, B. A. Johnson, J. D. Glass, and Q. Long, “Estimating the palliative effect of percutaneous endoscopic gastrostomy in an observational registry using principal stratification and generalized propensity scores,” Scientific Reports, vol. 6, 2016.
• V. Vaccarino, K. Wilmot, I. Al Mheid, R. Ramadan, P. Pimple, A. J. Shah, E. V. Garcia, J. Nye, L. Ward, M. Hammadah, and others, “Sex differences in mental stress-induced myocardial ischemia in patients with coronary heart disease,” Journal of the American Heart Association, vol. 5, iss. 9, p. e003630, 2016.
• I. Al Mheid, S. S. Hayek, Y. Ko, F. Akbik, Q. Li, N. Ghasemzadeh, G. S. Martin, Q. Long, M. Hammadah, M. A. Zafari, and others, “Age and human regenerative capacity impact of cardiovascular risk factorsnovelty and significance,” Circulation Research, vol. 119, iss. 7, pp. 801-809, 2016.

2015

• Q. Long and B. A. Johnson, “Variable selection in the presence of missing data: resampling and imputation,” Biostatistics, vol. 16, iss. 3, pp. 596-610, 2015.
• S. L. Jackson, Q. Long, M. K. Rhee, D. E. Olson, A. M. Tomolo, S. A. Cunningham, U. Ramakrishnan, K. V. Narayan, and L. S. Phillips, “Weight loss and incidence of diabetes with the veterans health administration move! lifestyle change programme: an observational study,” The Lancet Diabetes & Endocrinology, vol. 3, iss. 3, pp. 173-180, 2015.
• H. Tu, D. W. Flanders, T. U. Ahearn, C. R. Daniel, A. G. Gonzalez-Feliciano, Q. Long, R. E. Rutherford, and R. M. Bostick, “Effects of calcium and vitamin d3 on transforming growth factors in rectal mucosa of sporadic colorectal adenoma patients: a randomized controlled trial,” Molecular Carcinogenesis, vol. 54, iss. 4, pp. 270-280, 2015.
• H. Tu, L. Sun, X. Dong, Y. Gong, Q. Xu, J. Jing, Q. Long, D. W. Flanders, R. M. Bostick, and Y. Yuan, “Temporal changes in serum biomarkers and risk for progression of gastric precancerous lesions: a longitudinal study,” International Journal of Cancer, vol. 136, iss. 2, pp. 425-434, 2015.
• L. Merjaneh, Q. He, Q. Long, L. Phillips, and A. Stecenko, “Disposition index identifies defective beta-cell function in cystic fibrosis subjects with normal glucose tolerance,” Journal of Cystic Fibrosis, vol. 14, iss. 1, pp. 135-141, 2015.
• D. E. Olson, M. Zhu, Q. Long, D. Barb, J. S. Haw, M. K. Rhee, A. V. Mohan, P. I. Watson-Williams, S. L. Jackson, A. M. Tomolo, and others, “Increased cardiovascular disease, resource use, and costs before the clinical diagnosis of diabetes in veterans in the southeastern us,” Journal of General Internal Medicine, vol. 30, iss. 6, pp. 749-757, 2015.

2014

• Q. Long, J. Xu, A. O. Osunkoya, S. Sannigrahi, B. A. Johnson, W. Zhou, T. Gillespie, J. Y. Park, R. K. Nam, L. Sugar, and others, “Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence,” Cancer Research, vol. 74, iss. 12, pp. 3228-3237, 2014.
• Y. Deng, X. Zhang, and Q. Long, “Bayesian modeling and prediction of accrual in multi-regional clinical trials,” Statistical Methods in Medical Research, p. 962280214557581, 2014.
• C. Hsu, Q. Long, Y. Li, and E. Jacobs, “A nonparametric multiple imputation approach for data with missing covariate values with application to colorectal adenoma data,” Journal of Biopharmaceutical Statistics, vol. 24, iss. 3, pp. 634-648, 2014.
• H. Wasse, R. Huang, Q. Long, Y. Zhao, S. Singapuri, W. McKinnon, G. Skardasis, and V. Tangpricha, “Very high-dose cholecalciferol and arteriovenous fistula maturation in ESRD: a randomized, double-blind, placebo-controlled pilot study,” The Journal of Vascular Access, vol. 15, iss. 2, pp. 88-94, 2014.
• N. Dubowitz, W. Xue, Q. Long, J. Ownby, D. Olson, D. Barb, M. Rhee, A. Mohan, P. Watson-Williams, S. Jackson, and others, “Aging is associated with increased hba1c levels, independently of glucose levels and insulin resistance, and also with decreased hba1c diagnostic specificity,” Diabetic Medicine, vol. 31, iss. 8, pp. 927-935, 2014.

2013

• M. Chung, Q. Long, and B. A. Johnson, “A tutorial on rank-based coefficient estimation for censored data in small-and large-scale problems,” Statistics and Computing, vol. 23, iss. 5, pp. 601-614, 2013.
• W. Huang, S. Shah, Q. Long, A. K. Crankshaw, and V. Tangpricha, “Improvement of pain, sleep, and quality of life in chronic pain patients with vitamin d supplementation,” The Clinical Journal of Pain, vol. 29, iss. 4, pp. 341-347, 2013.
• H. Wasse, F. Cardarelli, C. De Staercke, C. W. Hooper, and Q. Long, “Accumulation of retained nonfunctional arteriovenous grafts correlates with severity of inflammation in asymptomatic esrd patients,” Nephrology Dialysis Transplantation, vol. 28, iss. 4, pp. 991-997, 2013.
• R. J. Chakkalakal, S. M. Higgins, L. B. Bernstein, K. L. Lundberg, V. Wu, J. Green, Q. Long, and J. P. Doyle, “Does patient gender impact resident physicians’ approach to the cardiac exam?,” Journal of General Internal Medicine, vol. 28, iss. 4, pp. 561-566, 2013.
• R. Chatterjee, K. V. Narayan, J. Lipscomb, S. L. Jackson, Q. Long, M. Zhu, and L. S. Phillips, “Screening for diabetes and prediabetes should be cost-saving in patients at high risk,” Diabetes Care, vol. 36, iss. 7, pp. 1981-1987, 2013.
• M. A. Torres, T. W. Pace, T. Liu, J. C. Felger, D. Mister, G. H. Doho, J. N. Kohn, A. M. Barsevick, Q. Long, and A. H. Miller, “Predictors of depression in breast cancer patients treated with radiation: role of prior chemotherapy and nuclear factor kappa b,” Cancer, vol. 119, iss. 11, pp. 1951-1959, 2013.
• D. Musselman, E. B. Royster, M. Wang, Q. Long, L. M. Trimble, T. K. Mann, D. S. Graciaa, M. D. McNutt, N. F. Auyeung, L. Oliver, and others, “The impact of escitalopram on il-2-induced neuroendocrine, immune, and behavioral changes in patients with malignant melanoma: preliminary findings,” Neuropsychopharmacology, vol. 38, iss. 10, pp. 1921-1928, 2013.
• W. Huang, D. L. Bliwise, T. M. Johnson, Q. Long, N. Kutner, and A. Y. Stringer, “Correlates of persistent sleep complaints after traumatic brain injury,” Neuropsychological Rehabilitation, vol. 23, iss. 5, pp. 698-714, 2013.

2012

• Q. Long, C. Hsu, and Y. Li, “Doubly robust nonparametric multiple imputation for ignorable missing data,” Statistica Sinica, vol. 22, pp. 149-172, 2012.
• Q. Long, “A note on generalized functional linear model and its application,” Journal of Statistical Planning and Inference, vol. 142, iss. 9, pp. 2599-2606, 2012.
• X. Zhang and Q. Long, “Modeling and prediction of subject accrual and event times in clinical trials: a systematic review,” Clinical Trials, vol. 9, iss. 6, pp. 681-688, 2012.
• M. Wang, W. Dana Flanders, R. M. Bostick, and Q. Long, “A conditional likelihood approach for regression analysis using biomarkers measured with batch-specific error,” Statistics in Medicine, vol. 31, iss. 29, pp. 3896-3906, 2012.
• X. Zhang and Q. Long, “Joint monitoring and prediction of accrual and event times in clinical trials,” Biometrical Journal, vol. 54, iss. 6, pp. 735-749, 2012.
• J. D. Newport, S. Ji, Q. Long, B. T. Knight, E. B. Zach, E. N. Smith, N. J. Morris, and Z. N. Stowe, “Maternal depression and anxiety differentially impact fetal exposures during pregnancy.,” The Journal of Clinical Psychiatry, vol. 73, iss. 2, pp. 247-251, 2012.
• C. Monk, J. D. Newport, J. H. Korotkin, Q. Long, B. Knight, and Z. N. Stowe, “Uterine blood flow in a psychiatric population: impact of maternal depression, anxiety, and psychotropic medication,” Biological Psychiatry, vol. 72, iss. 6, pp. 483-490, 2012.
• H. Wasse, R. Huang, Q. Long, S. Singapuri, P. Raggi, and V. Tangpricha, “Efficacy and safety of a short course of very-high-dose cholecalciferol in hemodialysis,” The American Journal of Clinical Nutrition, vol. 95, iss. 2, pp. 522-528, 2012.

2011

• Q. Long, M. Chung, C. S. Moreno, and B. A. Johnson, “Risk prediction for prostate cancer recurrence through regularized estimation with simultaneous adjustment for nonlinear clinical effects,” The Annals of Applied Statistics, vol. 5, iss. 3, pp. 2003-2023, 2011.
• Q. Long, B. A. Johnson, A. O. Osunkoya, Y. Lai, W. Zhou, M. Abramovitz, M. Xia, M. B. Bouzyk, R. K. Nam, L. Sugar, and others, “Protein-coding and microrna biomarkers of recurrence of prostate cancer following radical prostatectomy,” The American Journal of Pathology, vol. 179, iss. 1, pp. 46-54, 2011.
• Q. Long, X. Zhang, and B. A. Johnson, “Robust estimation of area under roc curve using auxiliary variables in the presence of missing biomarker values,” Biometrics, vol. 67, iss. 2, pp. 559-567, 2011.
• Q. Long, X. Zhang, and R. M. Bostick, “Semiparametric estimation for joint modeling of colorectal cancer risk and functional biomarkers measured with errors,” Biometrical Journal, vol. 53, iss. 3, pp. 393-410, 2011.
• M. Wang and Q. Long, “Modified robust variance estimator for generalized estimating equations with improved small-sample performance,” Statistics in Medicine, vol. 30, iss. 11, pp. 1278-1291, 2011.
• C. Hsu, Y. Li, Q. Long, Q. Zhao, and P. Lance, “Estimation of recurrence of colorectal adenomas with dependent censoring using weighted logistic regression,” Statistics in Medicine, vol. 6, iss. 10, p. e25141, 2011.
• Q. Long, X. Zhang, and C. Hsu, “Nonparametric multiple imputation for receiver operating characteristics analysis when some biomarker values are missing at random,” Statistics in Medicine, vol. 30, iss. 26, pp. 3149-3161, 2011.
• B. A. Johnson, Q. Long, and M. Chung, “On path restoration for censored outcomes,” Biometrics, vol. 67, iss. 4, pp. 1379-1388, 2011.
• B. A. Johnson and Q. Long, “Survival ensembles by the sum of pairwise differences with application to lung cancer microarray studies,” The Annals of Applied Statistics, vol. 5, iss. 2A, pp. 1081-1101, 2011.
• S. Ji, Q. Long, J. D. Newport, H. Na, B. Knight, E. B. Zach, N. J. Morris, M. Kutner, and Z. N. Stowe, “Validity of depression rating scales during pregnancy and the postpartum period: impact of trimester and parity,” Journal of Psychiatric Research, vol. 45, iss. 2, pp. 213-219, 2011.
• T. U. Ahearn, M. L. McCullough, D. W. Flanders, Q. Long, E. Sidelnikov, V. Fedirko, C. R. Daniel, R. E. Rutherford, A. Shaukat, and R. M. Bostick, “A randomized clinical trial of the effects of supplemental calcium and vitamin d3 on markers of their metabolism in normal mucosa of colorectal adenoma patients,” Cancer Research, vol. 71, iss. 2, pp. 413-423, 2011.
• S. H. Goodman, M. H. Rouse, Q. Long, S. Ji, and S. R. Brand, “Deconstructing antenatal depression: what is it that matters for neonatal behavioral functioning?,” Infant Mental Health Journal, vol. 32, iss. 3, pp. 339-361, 2011.
• H. Wasse, A. A. Rivera, R. Huang, D. E. Martinson, Q. Long, W. McKinnon, N. Naqvi, and A. Husain, “Increased plasma chymase concentration and mast cell chymase expression in venous neointimal lesions of patients with ckd and esrd,” Seminars in Dialysis, vol. 24, iss. 6, pp. 688-693, 2011.
• J. G. Twombly, Q. Long, M. Zhu, L. Fraser, D. E. Olson, P. W. Wilson, K. V. Narayan, and L. S. Phillips, “Validity of the primary care diagnosis of diabetes in veterans in the southeastern united states,” Diabetes Research and Clinical Practice, vol. 91, iss. 3, pp. 395-400, 2011.

2010

• Q. Long, R. J. Little, and X. Lin, “Estimating causal effects in trials involving multitreatment arms subject to non-compliance: a bayesian framework,” Journal of the Royal Statistical Society: Series C, vol. 59, iss. 3, pp. 513-531, 2010.
• Q. Long, D. W. Flanders, V. Fedirko, and R. M. Bostick, “Robust statistical methods for analysis of biomarkers measured with batch/experiment-specific errors,” Statistics in Medicine, vol. 29, iss. 3, pp. 361-370, 2010.
• X. Zhang and Q. Long, “Stochastic modeling and prediction for accrual in clinical trials,” Statistics in Medicine, vol. 29, iss. 6, pp. 649-658, 2010.
• V. Fedirko, R. M. Bostick, Q. Long, D. W. Flanders, M. L. McCullough, E. Sidelnikov, C. R. Daniel, R. E. Rutherford, and A. Shaukat, “Effects of supplemental vitamin d and calcium on oxidative dna damage marker in normal colorectal mucosa: a randomized clinical trial,” Cancer Epidemiology Biomarkers & Prevention, vol. 19, iss. 1, pp. 280-291, 2010.
• L. Cooper, D. A. Gutman, Q. Long, B. A. Johnson, S. R. Cholleti, T. Kurc, J. H. Saltz, D. J. Brat, and C. S. Moreno, “The proneural molecular signature is enriched in oligodendrogliomas and predicts improved survival among diffuse gliomas,” PLOS One, vol. 5, iss. 9, p. e12548, 2010.
• E. Sidelnikov, R. M. Bostick, D. W. Flanders, Q. Long, V. Fedirko, A. Shaukat, C. R. Daniel, and R. E. Rutherford, “Effects of calcium and vitamin d on mlh1 and msh2 expression in rectal mucosa of sporadic colorectal adenoma patients,” Cancer Epidemiology Biomarkers & Prevention, vol. 19, iss. 4, pp. 1022-1032, 2010.
• J. G. Twombly, Q. Long, M. Zhu, P. W. Wilson, K. V. Narayan, L. Fraser, B. C. Webber, and L. S. Phillips, “Diabetes care in black and white veterans in the southeastern us,” Diabetes Care, vol. 33, iss. 5, pp. 958-963, 2010.
• L. Fraser, J. Twombly, M. Zhu, Q. Long, J. J. Hanfelt, K. V. Narayan, P. W. Wilson, and L. S. Phillips, “Delay in diagnosis of diabetes is not the patient’s fault,” Diabetes Care, vol. 33, iss. 1, p. e10–e10, 2010.

2009

• R. J. Little, Q. Long, and X. Lin, “Discussion of “can nonrandomized experiments yield accurate answers? a randomized experiment comparing random to nonrandom assignments?" by Shadish, Clark and Steiner,” Journal of the American Statistical Association, vol. 103, iss. 484, pp. 1344-1346, 2009.
• R. J. Little, Q. Long, and X. Lin, “A comparison of methods for estimating the causal effect of a treatment in randomized clinical trials subject to noncompliance,” Biometrics, vol. 65, iss. 2, pp. 640-649, 2009.
• F. S. Auyeung, Q. Long, E. B. Royster, S. Murthy, M. D. McNutt, D. Lawson, A. Miller, A. Manatunga, and D. L. Musselman, “Sequential multiple-assignment randomized trial design of neurobehavioral treatment for patients with metastatic malignant melanoma undergoing high-dose interferon-alpha therapy,” Clinical Trials, vol. 6, iss. 5, pp. 480-490, 2009.
• C. Hsu, Q. Long, and D. S. Alberts, “Estimation of colorectal adenoma recurrence with dependent censoring,” BMC Medical Research Methodology, vol. 9, iss. 1, p. 66, 2009.
• C. Hsu, J. M. Taylor, Q. Long, and D. S. Alberts, “Analysis of colorectal adenoma recurrence data subject to informative censoring,” Cancer Epidemiology Biomarkers & Prevention, vol. 18, iss. 3, pp. 712-717, 2009.
• V. Fedirko, R. M. Bostick, D. W. Flanders, Q. Long, A. Shaukat, R. E. Rutherford, C. R. Daniel, V. Cohen, and C. Dash, “Effects of vitamin d and calcium supplementation on markers of apoptosis in normal colon mucosa: a randomized, double-blind, placebo-controlled clinical trial,” Cancer Prevention Research, vol. 2, iss. 3, pp. 213-223, 2009.
• V. Fedirko, R. M. Bostick, D. W. Flanders, Q. Long, E. Sidelnikov, A. Shaukat, C. R. Daniel, R. E. Rutherford, and J. J. Woodard, “Effects of vitamin d and calcium on proliferation and differentiation in normal colon mucosa: a randomized clinical trial,” Cancer Epidemiology Biomarkers & Prevention, vol. 18, iss. 11, pp. 2933-2941, 2009.
• C. R. Daniel, R. M. Bostick, W. D. Flanders, Q. Long, V. Fedirko, E. Sidelnikov, and M. E. Seabrook, “Tgf-$\alpha$ expression as a potential biomarker of risk within the normal-appearing colorectal mucosa of patients with and without incident sporadic adenoma,” Cancer Epidemiology, Biomarkers & Prevention, vol. 18, iss. 1, pp. 65-73, 2009.
• E. Sidelnikov, R. M. Bostick, D. W. Flanders, Q. Long, V. L. Cohen, C. Dash, M. E. Seabrook, and V. Fedirko, “Mutl-homolog 1 expression and risk of incident, sporadic colorectal adenoma: search for prospective biomarkers of risk for colorectal cancer,” Cancer Epidemiology Biomarkers & Prevention, vol. 18, iss. 5, pp. 1599-1609, 2009.
• E. Sidelnikov, R. M. Bostick, D. W. Flanders, Q. Long, and M. E. Seabrook, “Colorectal mucosal expression of msh2 as a potential biomarker of risk for colorectal neoplasms,” Cancer Epidemiology Biomarkers & Prevention, vol. 18, iss. 11, pp. 2965-2973, 2009.

2008

• Q. Long, R. Little, and X. Lin, “Causal inference in hybrid intervention trials involving treatment choice,” Journal of the American Statistical Association, vol. 103, iss. 482, pp. 474-484, 2008.
• N. M. Clark, N. K. Janz, J. A. Dodge, L. Mosca, X. Lin, Q. Long, R. J. Little, J. R. Wheeler, S. Keteyian, and J. Liang, “The effect of patient choice of intervention on health outcomes,” Contemporary Clinical Trials, vol. 29, iss. 5, pp. 679-686, 2008.

2007

• E. Sidelnikov, R. Bostick, Q. Long, and C. Dash, “Mlh1 levels in colon crypts and colon cancer risk factors in the markers of adenomatous polyps ii case-control study,” Cancer Research, vol. 67, iss. 9 Supplement, pp. 1712-1712, 2007.

2004

• K. R. Flaherty, T. E. King Jr, G. Raghu, J. P. Lynch III, T. V. Colby, W. D. Travis, B. H. Gross, E. A. Kazerooni, G. B. Toews, Q. Long, and others, “Idiopathic interstitial pneumonia: what is the effect of a multidisciplinary approach to diagnosis?,” American Journal of Respiratory and Critical Care Medicine, vol. 170, iss. 8, pp. 904-910, 2004.

2003

• V. N. Lama, K. R. Flaherty, G. B. Toews, T. V. Colby, W. D. Travis, Q. Long, S. Murray, E. A. Kazerooni, B. H. Gross, J. P. Lynch III, and others, “Prognostic value of desaturation during a 6-minute walk test in idiopathic interstitial pneumonia,” American Journal of Respiratory and Critical Care Medicine, vol. 168, iss. 9, pp. 1084-1090, 2003.
• K. K. Kim, K. R. Flaherty, Q. Long, N. Hattori, T. H. Sisson, T. V. Colby, W. D. Travis, F. J. Martinez, S. Murray, and R. H. Simon, “A plasminogen activator inhibitor-1 promoter polymorphism and idiopathic interstitial pneumonia,” Molecular Medicine, vol. 9, iss. 1-2, p. 52, 2003.