Shuangge Steven Ma, PhD
Research & Publications
Biography
News
Locations
Research Summary
I conduct independent research in multiple statistical areas, including bioinformatics, survival analysis, and semiparametric analysis with support from multiple funding agencies. I provide statistical support to multiple studies conducted at Yale and VA CT Healthcare System in the areas of cancer, mental disorders and health economics.
Extensive Research Description
Develop novel statistical methodologies for complex data;
Study epidemiology and pathogenesis of multiple cancers, including breast cancer, NHL, melanoma and lung cancer;
Conduct survey studies in mainland China and Taiwan, investigating health insurance utilization and impact;
Provide statistical support to multiple biomedical studies.
Coauthors
Research Interests
Economics; Neoplasms; Biostatistics
Public Health Interests
Bioinformatics; Biomarkers; Cancer; Cardiovascular Diseases; Genetics, Genomics, Epigenetics; Health Policy; Mental Health
Selected Publications
- A penalized integrative deep neural network for variable selection among multiple omics datasetsLi Y, Ren X, Yu H, Sun T, Ma S. A penalized integrative deep neural network for variable selection among multiple omics datasets. Quantitative Biology 2024 DOI: 10.1002/qub2.51.
- Partial Hepatectomy and Ablation for Survival of Early-Stage Hepatocellular Carcinoma Patients: A Bayesian Emulation AnalysisWang J, Im Y, Wang R, Ma S. Partial Hepatectomy and Ablation for Survival of Early-Stage Hepatocellular Carcinoma Patients: A Bayesian Emulation Analysis. Life 2024, 14: 661. DOI: 10.3390/life14060661.
- Prediction Consistency Regularization for Learning with Noise Labels Based on Contrastive ClusteringSun X, Zhang S, Ma S. Prediction Consistency Regularization for Learning with Noise Labels Based on Contrastive Clustering. Entropy 2024, 26: 308. PMID: 38667864, PMCID: PMC11049179, DOI: 10.3390/e26040308.
- Informationāincorporated sparse hierarchical cancer heterogeneity analysisHan W, Zhang S, Ma S, Ren M. Informationāincorporated sparse hierarchical cancer heterogeneity analysis. Statistics In Medicine 2024, 43: 2280-2297. PMID: 38553996, DOI: 10.1002/sim.10071.
- Organochlorine pesticides and risk of papillary thyroid cancer in U.S. military personnel: a nested case-control studyRusiecki J, McAdam J, Denic-Roberts H, Sjodin A, Davis M, Jones R, Hoang T, Ward M, Ma S, Zhang Y. Organochlorine pesticides and risk of papillary thyroid cancer in U.S. military personnel: a nested case-control study. Environmental Health 2024, 23: 28. PMID: 38504322, PMCID: PMC10949709, DOI: 10.1186/s12940-024-01068-0.
- Endocrine disrupting chemical mixture exposure and risk of papillary thyroid cancer in U.S. military personnel: A nested case-control studyDenic-Roberts H, McAdam J, Sjodin A, Davis M, Jones R, Ward M, Hoang T, Ma S, Zhang Y, Rusiecki J. Endocrine disrupting chemical mixture exposure and risk of papillary thyroid cancer in U.S. military personnel: A nested case-control study. The Science Of The Total Environment 2024, 922: 171342. PMID: 38428594, PMCID: PMC11034764, DOI: 10.1016/j.scitotenv.2024.171342.
- Estimation of multiple networks with common structures in heterogeneous subgroupsQin X, Hu J, Ma S, Wu M. Estimation of multiple networks with common structures in heterogeneous subgroups. Journal Of Multivariate Analysis 2024, 202: 105298. PMID: 38433779, PMCID: PMC10907012, DOI: 10.1016/j.jmva.2024.105298.
- Hierarchical false discovery rate control for high-dimensional survival analysis with interactionsLiang W, Zhang Q, Ma S. Hierarchical false discovery rate control for high-dimensional survival analysis with interactions. Computational Statistics & Data Analysis 2023, 192: 107906. PMID: 38098875, PMCID: PMC10718515, DOI: 10.1016/j.csda.2023.107906.
- FunctanSNP: an R package for functional analysis of dense SNP data (with interactions)Ren R, Fang K, Zhang Q, Ma S. FunctanSNP: an R package for functional analysis of dense SNP data (with interactions). Bioinformatics 2023, 39: btad741. PMID: 38060266, PMCID: PMC10723032, DOI: 10.1093/bioinformatics/btad741.
- EditorialMa S. Editorial. Briefings In Bioinformatics 2023, 24: bbad258. PMID: 37406189, DOI: 10.1093/bib/bbad258.
- Identifying Sex-Specific Cancer Metabolites and Associations to PrognosisShen X, Ma S, Khan S, Johnson C. Identifying Sex-Specific Cancer Metabolites and Associations to Prognosis. 2023, 271-299. DOI: 10.1007/978-3-031-44256-8_11.
- Heterogeneous Graphical Model for Non-Negative and Non-Gaussian PM2.5 dataZhang J, Fan X, Li Y, Ma S. Heterogeneous Graphical Model for Non-Negative and Non-Gaussian PM2.5 data. Journal Of The Royal Statistical Society Series C (Applied Statistics) 2022, 71: 1303-1329. DOI: 10.1111/rssc.12575.
- Network-adaptive robust penalized estimation of time-varying coefficient models with longitudinal dataFang K, Fan X, Ma S, Zhang Q. Network-adaptive robust penalized estimation of time-varying coefficient models with longitudinal data. Journal Of Statistical Computation And Simulation 2022, 92: 3045-3065. DOI: 10.1080/00949655.2022.2055758.
- A treeābased geneāenvironment interaction analysis with rare featuresLiu M, Zhang Q, Ma S. A treeābased geneāenvironment interaction analysis with rare features. Statistical Analysis And Data Mining The ASA Data Science Journal 2022, 15: 648-674. PMID: 38046814, PMCID: PMC10691867, DOI: 10.1002/sam.11578.
- Biclustering analysis of functionals via penalized fusionFang K, Chen Y, Ma S, Zhang Q. Biclustering analysis of functionals via penalized fusion. Journal Of Multivariate Analysis 2021, 189: 104874. PMID: 36817965, PMCID: PMC9937451, DOI: 10.1016/j.jmva.2021.104874.
- An association test for functional data based on Kendallās TauJadhav S, Ma S. An association test for functional data based on Kendallās Tau. Journal Of Multivariate Analysis 2021, 184: 104740. DOI: 10.1016/j.jmva.2021.104740.
- Promote sign consistency in the joint estimation of precision matricesZhang Q, Ma S, Huang Y. Promote sign consistency in the joint estimation of precision matrices. Computational Statistics & Data Analysis 2021, 159: 107210. DOI: 10.1016/j.csda.2021.107210.
- Conditional score matching for high-dimensional partial graphical modelsFan X, Zhang Q, Ma S, Fang K. Conditional score matching for high-dimensional partial graphical models. Computational Statistics & Data Analysis 2021, 153: 107066. DOI: 10.1016/j.csda.2020.107066.
- An Application of the Cure Model to a Cardiovascular Clinical TrialSevilimedu V, Ma S, Hartigan P, Kyriakides T. An Application of the Cure Model to a Cardiovascular Clinical Trial. Statistics In Biosciences 2020, 13: 402-430. DOI: 10.1007/s12561-020-09297-w.
- Functional measurement error in functional regressionJadhav S, Ma S. Functional measurement error in functional regression. Canadian Journal Of Statistics 2020, 48: 238-258. DOI: 10.1002/cjs.11529.
- A modified mean-variance feature-screening procedure for ultrahigh-dimensional discriminant analysisHe S, Ma S, Xu W. A modified mean-variance feature-screening procedure for ultrahigh-dimensional discriminant analysis. Computational Statistics & Data Analysis 2019, 137: 155-169. DOI: 10.1016/j.csda.2019.02.003.
- Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative ModelZhang T, Huang Y, Zhang Q, Ma S, Ahmed S. Penalized Relative Error Estimation of a Partially Functional Linear Multiplicative Model. 2019, 127-144. DOI: 10.1007/978-3-030-17519-1_10.
- Variable selection and direction estimation for single-index models via DC-TGDR methodZhong W, Liu X, Ma S. Variable selection and direction estimation for single-index models via DC-TGDR method. Statistics And Its Interface 2018, 11: 169-181. DOI: 10.4310/sii.2018.v11.n1.a14.
- 2432Huang Y, Brown S, Ma S, Kyriakides T. 2432. Journal Of Clinical And Translational Science 2017, 1: 37-37. PMCID: PMC6799711, DOI: 10.1017/cts.2017.137.
- Identifying GeneāEnvironment Interactions Associated with Prognosis Using Penalized Quantile RegressionWang G, Zhao Y, Zhang Q, Zang Y, Zang S, Ma S. Identifying GeneāEnvironment Interactions Associated with Prognosis Using Penalized Quantile Regression. 2017, 347-367. DOI: 10.1007/978-3-319-41573-4_17.