Publications
publications.RmdAll the publications can also be found in my cv ordered by time
Student's name
Variable Selection
Lu M., Sha Y., Silva T.C., Colaprico A., Sun X., Ban Y., Wang L., Lehmann B.D. and Chen X.S. (2021). LR Hunting: A Random Forest Based Cell–Cell Interaction Discovery Method for Single-Cell Gene Expression Data. Frontiers in Genetics. 2021 Aug 20;12:708835. [pdf] [url] [.bib cite /exp]
Lu M. and Ishwaran H. (2021). Discussion of nonparametric variable importance assessment. Biometrics, 77: 23-27. [pdf] [url] [.bib cite /exp]
Lu M. and Ishwaran H. (2018). A Prediction-Based Alternative to P-values in Regression Models.} The Journal of Thoracic and Cardiovascular Surgery, 155: 1130-1136. [pdf] [url] [arXiv] [.bib cite /exp]
Lu M. and Ishwaran H. (2021). Tree Variable Selection for Paired Case-Control Studies with Application to Microbiome Data. In Statistical Analysis of Microbiome Data, eds. S. Datta and S. Guha (Springer, Switzerland), chapter 12, 295–310. [url] [pdf] [.bib cite /exp] [ebook]
COVID-19
Lu M. and Liao X. (2022). Access to Care Through Telehealth Among U.S. Medicare Beneficiaries in the Wake of the COVID-19 Pandemic. Frontiers in Public Health 10:946944. [pdf] [supplemental pdf] [url] [.bib cite /exp]
Lu M. and Ishwaran H. (2021). Cure and death play a role in understanding dynamics for COVID-19: data-driven competing risk compartmental models, with and without vaccination. PloS one 16(7): e0254397. [pdf] [supplemental pdf] [url] [.bib cite /exp]
Lu M. (2020). Dynamic Modeling COVID-19 for Comparing Containment Strategies in a Pandemic Scenario. Annals of Biostatistics & Biometric Application 4(1):1–4. [pdf] [url] [.bib cite /exp]
Yurekli H, Yiğit E.O., Bulut O., Lu M. and Ersoy Öz E. (2022). Exploring Factors that Affect Student Well-Being during the COVID-19 Pandemic: A Comparison of Data Mining Approaches. International Journal of Environmental Research and Public Health 19(18): 11267. [pdf] [url] [.bib cite /exp]
Random Forests
Lu M. Yin R. and Chen X.S. (2024). Ensemble Methods of Rank-Based Trees for Single Sample Classification with Gene Expression Profiles. Journal of Translational Medicine. 22:140. [url] [pdf][CRAN Package] [.bib cite /exp]
Ishwaran H. and Lu M. (2019). Standard Errors and Confidence Intervals for Variable Importance in Random Forest Regression, Classification, and Survival. Statistics in Medicine, 38: 558-582. [pdf] [url] [.bib cite /exp]
Ishwaran H. and Lu M. (2019). Random Survival Forests. Wiley StatsRef: Statistics Reference Online, 1-13. [pdf] [url] [.bib cite /exp]
Causal Inference
Lu M., Sadiq S., Feaster D.J. and Ishwaran H. (2018). Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods. Journal of Computational and Graphical Statistics, 27: 209-219. [pdf] [url] [.bib cite /exp]
Lu M. (2018). Estimating Individual Treatment Effect in Observational Data Using Random Forest Methods. PhD dissertation, Univeristy of Miami [pdf] [url] [.bib cite /exp]
Feaster D.J., Ishwaran H., Lu M. and Sadiq S. (2020). New Statistical Methods to Assess How Patients with Different Traits Respond to the Same Treatment. Patient-Centered Outcomes Research Institute (PCORI). [url] [pdf] [.bib cite /exp]
Application
Alnajar A, Benck K.N., Dar T, Hirji S.A., Ibrahim W., Detweiler B., Vuddanda V., Balise R., Rao J.S, Lu M., Lamelas J., (2023) Predictors of Outcomes in Patients with Obesity Following Mitral Valve Surgery. The Journal of Thoracic and Cardiovascular Surgery (JTCVS) Open. 10:1016. [url]
Raja, S., Rice, T. W., Lu, M., Semple, M. E., Blackstone, E. H., Murthy, S. C., Ahmad, U., McNamara, M., Toth, A. J., Ishwaran, H. Adjuvant Therapy after Neoadjuvant Therapy for Esophageal Cancer: Who Needs It? Annals of Surgery. (in press).[pdf] [url]
Lu M. and Liao X. (2023). Telehealth Utilization in U.S. Medicare Beneficiaries Aged 65 Years and Older During the COVID-19 Pandemic. BMC Public Health. 23:368-382. [pdf] [supplemental pdf] [url] [.bib cite /exp]
Gonzalez-Guarda, R.M., McCabe, B., Nagy, G., Stafford, A., Lisvel, M., Lu, M., Felsman, R., Rocha-Goldberg, P., & Cervantes, R. (2023). Acculturative Stress, Resilience and a Syndemic Factor among Latinx Immigrants. Nursing Research. 72(2): p 249-258. [pdf] [url] [.bib cite /exp]
Lu M., Parel J.M., and Miller D. (2021). Interactions between staphylococcal enterotoxins A and D and superantigen-like proteins 1 and 5 for predicting methicillin and multidrug resistance profiles among Staphylococcus aureus ocular isolates. PloS one. 2021 Jul 28;16(7):e0254519. [pdf] [url] [.bib cite /exp]
Rice T.W., Lu M, Ishwaran H., and Blackstone, E.H. (2019). Precision Surgical Therapy for Adenocarcinoma of the Esophagus and Esophagogastric Junction: A Machine Learning Causal Analysis. Journal of Thoracic Oncology, 14(12): 2164-2175. [pdf] [url] [.bib cite /exp]
Software
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: getting started with randomForestSRC vignette.” Available from: http://randomforestsrc.org/articles/getstarted.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: installing randomForestSRC vignette.” Available from: http://randomforestsrc.org/articles/installation.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: parallel processing vignette.” Available from: http://randomforestsrc.org/articles/parallel.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: hybrid parallel processing vignette.” Available from: http://randomforestsrc.org/articles/hybrid.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: randomForestSRC algorithm vignette.” Available from: http://randomforestsrc.org/articles/algorithm.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: speedup random forest analyses vignette.” Available from: http://randomforestsrc.org/articles/speedup.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: forest weights, in-bag (IB) and out-of-bag (OOB) ensembles vignette.” Available from: http://randomforestsrc.org/articles/forestWgt.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lauer M.S., Blackstone E.H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: random survival forests vignette.” Available from: http://randomforestsrc.org/articles/survival.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Gerds T.A., Lau B.M., Lu M. and Kogalur U.B. (2021). “randomForestSRC: competing risks vignette.” Available from: http://randomforestsrc.org/articles/competing.html [pdf] [url] [.bib cite /exp]
Ishwaran H., O’Brien R., Lu M. and Kogalur U.B. (2021). “randomForestSRC: random forests quantile classifier (RFQ) vignette.” Available from: http://randomforestsrc.org/articles/imbalance.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Tang F., Lu M. and Kogalur U.B. (2021). “randomForestSRC: multivariate splitting rule vignette.” Available from: http://randomforestsrc.org/articles/mvsplit.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2022). “randomForestSRC: AUC splitting for multiclass problems vignette.” Available from: http://randomforestsrc.org/articles/aucsplit.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Mantero A., Lu M. and Kogalur U.B. (2021). “randomForestSRC: sidClustering vignette.” Available from: http://randomforestsrc.org/articles/sidClustering.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: variable importance (VIMP) with subsampling inference vignette.” Available from: http://randomforestsrc.org/articles/rfsrc-subsample.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Chen X., Minn A.J., Lu M., Lauer M.S. and Kogalur U.B. (2021). “randomForestSRC: minimal depth vignette.” Available from: http://randomforestsrc.org/articles/minidep.html [pdf] [url] [.bib cite /exp]
Ishwaran H., Lu M. and Kogalur U.B. (2021). “randomForestSRC: partial plots vignette.” Available from: http://randomforestsrc.org/articles/partial.html [pdf] [url] [.bib cite /exp]
Meta-Analysis
Lu M. (2023). Computing Within-Study Covariances, Data Visualization and Missing Data Solutions for Multivariate Meta-Analysis with metavcov Frontiers in Psychology. 2023 Jun 20;14:1185012. [url] [pdf] [R code tutorial][CRAN Package] [Website][.bib cite /exp]
Lu M. (2017). Variance-Covariance Matrix for Multivariate Meta-Analysis with R package metavcov. R package version 2.1. Available from https://cran.r-project.org/package=metavcov [pdf] [url] [.bib cite /exp]
Ahn S., Lu M., Lefevor G.T., Fedewa A.L. and Celimli S. (2015). “Application of Meta-Analysis in Sport and Exercise Science.” In An introduction to intermediate and advanced statistical analyses for sport and exercise scientists, eds. Ntoumanis N and Myers ND (John Wiley & Sons), chapter 11, 233–253. [url] [.bib cite /exp]
Other Publications
Zhai X. and Lu M. (2023). Editorial: Machine Learning Applications in Educational Studies. Frontiers in Education, 8: 1225802. [pdf] [url] [.bib cite /exp]
Myers N.D., Ahn S., Lu M., Celimli S., and Zopluoglu C. (2017). Reordering and Reflecting Factors for Simulation Studies with Exploratory Factor Analysis. Structural Equation Modeling: A Multidisciplinary Journal, 24: 112-128. [pdf] [url] [.bib cite /exp]
Ahn S., Zopluoglu C., Celimli S., Lu M., and Myers N.D. (2016). REREFACT: Reordering and/or Reflecting Factors for Simulation Studies with Exploratory Factor Analysis. R package version 1.0. Available from https://cran.r-project.org/package=REREFACT [pdf] [url] [.bib cite /exp]
Lu M. and Qin X. (2008). “Segmentation in the Mortgage Market: A Study of Pre-adjustment of Variables in Cluster Analysis”. In New Progress in Mathematics and Information Science, eds. Li Z et. al (Beijing University of Posts and Telecommunications Press), 339-355. (ISBN978-7-5635-1508-0) [url]
