Arnab Maity

Rose, D. K., Bentley, L., Maity, A., Maguire, R. L., Planchart, A., Spasojevic, I., … Hoyo, C. (2024). Association between F2-isoprostanes and self-reported stressors in pregnant americans of African and European ancestry. HELIYON, 10(3). https://doi.org/10.1016/j.heliyon.2024.e25578

Ghosal, R., & Maity, A. (2023, September 13). Variable selection in function-on-scalar single-index model via the alternating direction method of multipliers. TEST, Vol. 9. https://doi.org/10.1007/s11749-023-00884-9

Ghosal, R., & Maity, A. (2022). A Score Based Test for Functional Linear Concurrent Regression. ECONOMETRICS AND STATISTICS, 21, 114–130. https://doi.org/10.1016/j.ecosta.2021.05.003

Li, M., Wang, K., Maity, A., & Staicu, A.-M. (2022). Inference in functional linear quantile regression. JOURNAL OF MULTIVARIATE ANALYSIS, 190. https://doi.org/10.1016/j.jmva.2022.104985

Gonzalez-Nahm, S., Marchesoni, J., Maity, A., Maguire, R. L., House, J. S., Tucker, R., … Hoyo, C. (2022). Maternal Mediterranean Diet Adherence and Its Associations with Maternal Prenatal Stressors and Child Growth. CURRENT DEVELOPMENTS IN NUTRITION, 6(11). https://doi.org/10.1093/cdn/nzac146

Alam, K., Maity, A., Sinha, S. K., Rizopoulos, D., & Sattar, A. (2021). Joint modeling of longitudinal continuous, longitudinal ordinal, and time-to-event outcomes. LIFETIME DATA ANALYSIS, 27(1), 64–90. https://doi.org/10.1007/s10985-020-09511-3

Mehrotra, S., & Maity, A. (2021, November 22). Simultaneous variable selection, clustering, and smoothing in function-on-scalar regression. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, Vol. 11. https://doi.org/10.1002/cjs.11668

Ghosal, R., & Maity, A. (2021, September 27). Variable selection in nonlinear function-on-scalar regression. BIOMETRICS, Vol. 9. https://doi.org/10.1111/biom.13564

Ghosal, R., & Maity, A. (2021, September 24). Variable selection in nonparametric functional concurrent regression. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, Vol. 9. https://doi.org/10.1002/cjs.11654

Martinez, K., Maity, A., Yolken, R. H., Sullivan, P. F., & Tzeng, J.-Y. (2020). Robust kernel association testing (RobKAT). GENETIC EPIDEMIOLOGY, 44(3), 272–282. https://doi.org/10.1002/gepi.22280

Ghosal, R., Maity, A., Clark, T., & Longo, S. B. (2020). Variable selection in functional linear concurrent regression. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, 69(3), 565–587. https://doi.org/10.1111/rssc.12408

Zhao, N., Zhang, H., Clark, J. J., Maity, A., & Wu, M. C. (2019). Composite kernel machine regression based on likelihood ratio test for joint testing of genetic and gene–environment interaction effect. Biometrics, 75(2), 625–637. https://doi.org/10.1111/biom.13003

Szatkiewicz, J., Marceau, R., Yilmaz, Z., Bulik, C., Crowley, J., Mattheisen, M., … al. (2019). VARIANCE COMPONENT TEST FOR CROSS-DISORDER PATHWAY ANALYSIS. EUROPEAN NEUROPSYCHOPHARMACOLOGY, Vol. 29, pp. 1204–1205. https://doi.org/10.1016/j.euroneuro.2018.08.252

Tekbudak, M. Y., Alfaro-Córdoba, M., Maity, A., & Staicu, A.-M. (2018). A comparison of testing methods in scalar-on-function regression. AStA Advances in Statistical Analysis, 103(3), 411–436. https://doi.org/10.1007/s10182-018-00337-x

Kim, J. S., Staicu, A.-M., Maity, A., Carroll, R. J., & Ruppert, D. (2018). Additive Function-on-Function Regression. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 27(1), 234–244. https://doi.org/10.1080/10618600.2017.1356730

Kim, J. S., Maity, A., & Staicu, A.-M. (2018). Additive nonlinear functional concurrent model. Statistics and Its Interface, 11(4), 669–685. https://doi.org/10.4310/SII.2018.v11.n4.a11

Bandyopadhyay, S., & Maity, A. (2018). Asymptotic theory for varying coefficient regression models with dependent data. Annals of the Institute of Statistical Mathematics, 70(4), 745–759. https://doi.org/10.1007/s10463-017-0607-z

Paul, E., Maity, A. K., & Maiti, R. (2018). Bayesian comparative study on binary time series. Journal of Statistical Computation and Simulation, 88(14), 2811–2826. https://doi.org/10.1080/00949655.2018.1488256

Maity, A. K., Pradhan, V., & Das, U. (2018). Bias Reduction in Logistic Regression with Missing Responses When the Missing Data Mechanism is Nonignorable. The American Statistician, 73(4), 340–349. https://doi.org/10.1080/00031305.2017.1407359

Davenport, C. A., Maity, A., & Baladandayuthapani, V. (2018). Functional interaction-based nonlinear models with application to multiplatform genomics data. STATISTICS IN MEDICINE, 37(18), 2715–2733. https://doi.org/10.1002/sim.7671

Maity, A., Zhao, J., Sullivan, P. F., & Tzeng, J.-Y. (2018). Inference on phenotype-specific effects of genes using multivariate kernel machine regression. GENETIC EPIDEMIOLOGY, 42(1), 64–79. https://doi.org/10.1002/gepi.22096

Luo, Y., Maity, A., Wu, M. C., Smith, C., Duan, Q., Li, Y., & Tzeng, J.-Y. (2018). On the substructure controls in rare variant analysis: Principal components or variance components? GENETIC EPIDEMIOLOGY, 42(3), 276–287. https://doi.org/10.1002/gepi.22102

Kong, D., Maity, A., Hsu, F.-C., & Tzeng, J.-Y. (2018, June). Rejoinder to "A note on testing and estimation in marker-set association study using semiparametric quantile regression kernel machine". https://doi.org/10.1111/biom.12786

Davenport, C. A., Maity, A., Sullivan, P. F., & Tzeng, J.-Y. (2017). A Powerful Test for SNP Effects on Multivariate Binary Outcomes Using Kernel Machine Regression. Statistics in Biosciences, 10(1), 117–138. https://doi.org/10.1007/s12561-017-9189-9

Zhan, X., Tong, X., Zhao, N., Maity, A., Wu, M. C., & Chen, J. (2017). A small-sample multivariate kernel machine test for microbiome association studies. GENETIC EPIDEMIOLOGY, 41(3), 210–220. https://doi.org/10.1002/gepi.22030

Luo, Y., McCullough, L. E., Tzeng, J.-Y., Darrah, T., Vengosh, A., Maguire, R. L., … Hoyo, C. (2017). Maternal blood cadmium, lead and arsenic levels, nutrient combinations, and offspring birthweight. BMC Public Health, 17(1). https://doi.org/10.1186/s12889-017-4225-8

Maity, A. (2017). Nonparametric functional concurrent regression models. WIREs Computational Statistics, 9(2). https://doi.org/10.1002/wics.1394

Maity, A. (2017). [Review of Nonparametric functional concurrent regression models]. Wiley Interdisciplinary Reviews: Computational Statistics, 9(2).

Terry, W., Zhang, H., Maity, A., Arshad, H., & Karmaus, W. (2017). Unified variable selection in semi-parametric models. STATISTICAL METHODS IN MEDICAL RESEARCH, 26(6), 2821–2831. https://doi.org/10.1177/0962280215610928

Kong, D., Staicu, A.-M., & Maity, A. (2016). Classical testing in functional linear models. JOURNAL OF NONPARAMETRIC STATISTICS, 28(4), 813–838. https://doi.org/10.1080/10485252.2016.1231806

Usset, J., Staicu, A.-M., & Maity, A. (2016). Interaction models for functional regression. Computational Statistics & Data Analysis, 94, 317–329. https://doi.org/10.1016/j.csda.2015.08.020

Tzeng, J. Y., & Maity, A. (2016). Marker-set Approaches for Assessing Gene-Environment Interactions at Gene Level. In Statistical Approaches to Gene x Environment Interactions for Complex Phenotypes.

Kong, D., Maity, A., Hsu, F. C., Tzeng, J. Y., & Biometrics. (2016). Testing and estimation in marker-set association study using semiparametric quantile regression kernel machine. BIOMETRICS, 72(2), 364–371. https://doi.org/10.1111/biom.12438

Zhang, Y., Staicu, A.-M., & Maity, A. (2016). Testing for additivity in non-parametric regression. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 44(4), 445–462. https://doi.org/10.1002/cjs.11295

Zhang, H., MAITY, A. R. N. A. B., Arshad, H., Holloway, J., Karmaus, W., Lawson, A. B., … MacNab, Y. (2016). Variable selection in semi-parametric models. STATISTICAL METHODS IN MEDICAL RESEARCH, 25(4), 1736–1752. https://doi.org/10.1177/0962280213499679

Wang, Z., Maity, A., Luo, Y., Neely, M. L., & Tzeng, J.-Y. (2015). Complete Effect-Profile Assessment in Association Studies With Multiple Genetic and Multiple Environmental Factors. GENETIC EPIDEMIOLOGY, 39(2), 122–133. https://doi.org/10.1002/gepi.21877

Usset, J., Maity, A., Staicu, A.-M., & Schwartzman, A. (2015). Glacier Terminus Estimation from Landsat Image Intensity Profiles. Journal of Agricultural, Biological, and Environmental Statistics, 20(2), 279–298. https://doi.org/10.1007/s13253-015-0207-4

Zhao, N., Bell, D. A., Maity, A., Staicu, A.-M., Joubert, B. R., London, S. J., & Wu, M. C. (2015). Global Analysis of Methylation Profiles From High Resolution CpG Data. GENETIC EPIDEMIOLOGY, 39(2), 53–64. https://doi.org/10.1002/gepi.21874

Wang, Z., Maity, A., Hsiao, C. K., Voora, D., Kaddurah-Daouk, R., & Tzeng, J. Y. (2015). Module-based association analysis for omics data with network structure. PLoS ONE, 10(3), 0122309. https://doi.org/10.1371/journal.pone.0122309

Davenport, C. A., Maity, A., & Wu, Y. (2015). Parametrically guided estimation in nonparametric varying coefficient models with quasi-likelihood. JOURNAL OF NONPARAMETRIC STATISTICS, 27(2), 195–213. https://doi.org/10.1080/10485252.2015.1026903

Urrutia, E., Lee, S., Maity, A., Zhao, N., Shen, J., Li, Y., & Wu, M. C. (2015). Rare variant testing across methods and thresholds using the multi-kernel sequence kernel association test (MK-SKAT). STATISTICS AND ITS INTERFACE, 8(4), 495–505. https://doi.org/10.4310/sii.2015.v8.n4.a8

Maity, A., Williams, P. L., Ryan, L., Missmer, S. A., Coull, B. A., & Hauser, R. (2014). Analysis of in vitro fertilization data with multiple outcomes using discrete time-to-event analysis. STATISTICS IN MEDICINE, 33(10), 1738–1749. https://doi.org/10.1002/sim.6050

Carmona, J. J., Sofer, T., Hutchinson, J., Cantone, L., Coull, B., Maity, A., … al. (2014). Short-Term airborne particulate matter exposure alters the epigenetic landscape of human genes associated with the mitogen-Activated protein kinase network: A cross-sectional study. Environmental Health: A Global Access Science Source, 13(1), 94. https://doi.org/10.1186/1476-069X-13-94

Liu, C.-Y., Maity, A., Lin, X., Wright, R., & Christiani, D. (2013). Design and Analysis Issues in Gene and Environment Studies. Exploring Connections Between Genetic Mechanisms and Disease Expression, Vol. 11, p. 339–370. https://doi.org/10.1201/b16304-14

Sofer, T., Baccarelli, A., Cantone, L., Coull, B., Maity, A., Lin, X., & Schwartz, J. (2013). Exposure to airborne particulate matter is associated with methylation pattern in the asthma pathway. EPIGENOMICS, 5(2), 147–154. https://doi.org/10.2217/epi.13.16

Wu, M. C., Maity, A., Lee, S., Simmons, E. M., Harmon, Q. E., Lin, X., … Armistead, P. M. (2013). Kernel Machine SNP-Set Testing Under Multiple Candidate Kernels. GENETIC EPIDEMIOLOGY, 37(3), 267–275. https://doi.org/10.1002/gepi.21715

Xun, X., Cao, J., Mallick, B., Maity, A., & Carroll, R. J. (2013). Parameter Estimation of Partial Differential Equation Models. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 108(503), 1009–1020. https://doi.org/10.1080/01621459.2013.794730

Fan, J., Maity, A., Wang, Y., & Wu, Y. (2013). Parametrically guided generalised additive models with application to mergers and acquisitions data. JOURNAL OF NONPARAMETRIC STATISTICS, 25(1), 109–128. https://doi.org/10.1080/10485252.2012.735233

Gertheiss, J., Maity, A., & Staicu, A.-M. (2013). Variable selection in generalized functional linear models. Stat, 2(1), 86–101. https://doi.org/10.1002/sta4.20

Maity, A. (2012). A powerful test for comparing multiple regression functions. JOURNAL OF NONPARAMETRIC STATISTICS, 24(3), 563–576. https://doi.org/10.1080/10485252.2012.677842

Mahalingaiah, S., Missmer, S. A., Maity, A., Williams, P. L., Meeker, J. D., Berry, K., … al. (2012). Association of Hexachlorobenzene (HCB), Dichlorodiphenyltrichloroethane (DDT), and Dichlorodiphenyldichloroethylene (DDE) with in Vitro Fertilization (IVF) Outcomes. ENVIRONMENTAL HEALTH PERSPECTIVES, 120(2), 316–320. https://doi.org/10.1289/ehp.1103696

Liu, C.-Y., Maity, A., Lin, X., Wright, R. O., & Christiani, D. C. (2012). Design and analysis issues in gene and environment studies. Environmental Health: A Global Access Science Source, 11(1). https://doi.org/10.1186/1476-069X-11-93

Liu, C. Y., Maity, A., Lin, X. H., Wright, R. O., & Christiani, D. C. (2012). [Review of Design and analysis issues in gene and environment studies]. Environmental Health, 11.

Sofer, T., Maity, A., Coull, B., Baccarelli, A. A., Schwartz, J., & Lin, X. (2012). Multivariate Gene Selection and Testing in Studying the Exposure Effects on a Gene Set. Statistics in Biosciences, 4(2), 319–338. https://doi.org/10.1007/s12561-012-9072-7

Maity, A., Sullivan, P. E., & Tzeng, J.-Y. (2012). Multivariate Phenotype Association Analysis by Marker-Set Kernel Machine Regression. GENETIC EPIDEMIOLOGY, 36(7), 686–695. https://doi.org/10.1002/gepi.21663

Maity, A., & Huang, J. Z. (2012). Partially linear varying coefficient models stratified by a functional covariate. STATISTICS & PROBABILITY LETTERS, 82(10), 1807–1814. https://doi.org/10.1016/j.spl.2012.06.002

He, H., Zhang, H., Maity, A., Zou, Y., Hussey, J., & Karmaus, W. (2012). Power of a reproducing kernel-based method for testing the joint effect of a set of single-nucleotide polymorphisms. GENETICA, 140(10-12), 421–427. https://doi.org/10.1007/s10709-012-9690-5

Maity, A., & Sherman, M. (2012). Testing for spatial isotropy under general designs. Journal of Statistical Planning and Inference, 142(5), 1081–1091. https://doi.org/10.1016/j.jspi.2011.11.013

Bandyopadhyay, S., & Maity, A. (2011). Analysis of Sabine river flow data using semiparametric spline modeling. JOURNAL OF HYDROLOGY, 399(3-4), 274–280. https://doi.org/10.1016/j.jhydrol.2011.01.006

Maity, A., & Apanasovich, T. V. (2011). Estimation via corrected scores in general semiparametric regression models with error-prone covariates. ELECTRONIC JOURNAL OF STATISTICS, 5, 1424–1449. https://doi.org/10.1214/11-ejs647

Sherman, M., Maity, A., & Wang, S. (2011). Inferences for the ratio: Fieller's interval, log ratio, and large sample based confidence intervals. ASTA-ADVANCES IN STATISTICAL ANALYSIS, 95(3), 313–323. https://doi.org/10.1007/s10182-011-0162-5

Maity, A., & Lin, X. (2011). Powerful Tests for Detecting a Gene Effect in the Presence of Possible Gene-Gene Interactions Using Garrote Kernel Machines. BIOMETRICS, 67(4), 1271–1284. https://doi.org/10.1111/j.1541-0420.2011.01598.x

Perry, M. J., Chen, X., McAuliffe, M. E., Maity, A., & Deloid, G. M. (2011). Semi-Automated Scoring of Triple-probe FISH in Human Sperm: Methods and Further Validation. CYTOMETRY PART A, 79A(8), 661–666. https://doi.org/10.1002/cyto.a.21078

Meeker, J. D., Maity, A., Missmer, S. A., Williams, P. L., Mahalingaiah, S., Ehrlich, S., … Hauser, R. (2011). Serum Concentrations of Polychlorinated Biphenyls in Relation to in Vitro Fertilization Outcomes. ENVIRONMENTAL HEALTH PERSPECTIVES, 119(7), 1010–1016. https://doi.org/10.1289/ehp.1002922

Wei, J., Carroll, R. J., & Maity, A. (2011). Testing for constant nonparametric effects in general semiparametric regression models with interactions. STATISTICS & PROBABILITY LETTERS, 81(7), 717–723. https://doi.org/10.1016/j.spl.2010.11.002

Schwartz, J., Sofer, T., Maity, A., Lin, X., & Baccarelli, A. (2010). Particulate Air Pollution Modifies Methylation Of NFKb Pathways. C16. GENETICS OF LUNG DISEASE AND GENE: ENVIRONMENT INTERACTIONS, 5. https://doi.org/10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a4008

Dey, D., Ghosh, S., & Mallick, B. K. (2010). Proportional Hazards Regression Using Bayesian Kernel Machines. In Bayesian Modeling in Bioinformatics. https://doi.org/10.1201/EBK1420070170.

Zhou, L., Huang, J. Z., Martinez, J. G., Maity, A., Baladandayuthapani, V., & Carroll, R. J. (2010). Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data. Journal of the American Statistical Association, 105(489), 390–400. https://doi.org/10.1198/jasa.2010.tm08737

Carroll, R., Maity, A., Mammen, E., & Yu, K. (2009). Efficient Semiparametric Marginal Estimation for the Partially Linear Additive Model for Longitudinal/Clustered Data. Stat Biosci, 1(1), 10–31. https://doi.org/10.1007/s12561-009-9000-7

Carroll, R. J., Maity, A., Mammen, E., & Yu, K. (2009). Nonparametric Additive Regression for Repeatedly Measured Data. Biometrika, 96(2), 383–398. https://doi.org/10.1093/biomet/asp015

Apanasovich, T. V., Carroll, R. J., & Maity, A. (2009). SIMEX and standard error estimation in semiparametric measurement error models. Electronic Journal of Statistics, 3(0), 318–348. https://doi.org/10.1214/08-ejs341

Maity, A., Carroll, R. J., Mammen, E., & Chatterjee, N. (2009). Testing in semiparametric models with interaction, with applications to gene-environment interactions. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 71(1), 75–96. https://doi.org/10.1111/j.1467-9868.2008.00671.x

Efficient Inference in General Semiparametric Regression Models. (2008). Retrieved from http://oaktrust.library.tamu.edu/handle/1969.1/ETD-TAMU-3075

Maity, A. (2008). Efficient estimation of population quantiles in general semiparametric regression models. Statistics and Probability Letters, 78(16), 2744–2750. https://doi.org/10.1016/j.spl.2008.03.022

Maity, A., Apanasovich, T. V., & Carroll, R. J. (2008). Estimation of population-level summaries in general semiparametric repeated measures regression models. Collections, p. 123–137. https://doi.org/10.1214/193940307000000095

Maity, A., & Sherman, M. (2008). On adaptive linear regression. Journal of Applied Statistics, 35(12), 1409–1422. https://doi.org/10.1080/02664760802382475

Carroll, R. J., & Maity, A. (2007). Comments on: Nonparametric inference with generalized likelihood ratio tests. Test, 16(3), 456–458. https://doi.org/10.1007/s11749-007-0085-3

Maity, A., Ma, Y., & Carroll, R. J. (2007). Efficient estimation of population-level summaries in general semiparametric regression models. Journal of the American Statistical Association, 102(477), 123–139. https://doi.org/10.1198/016214506000001103

Maity, A., & Sherman, M. (2006). The two-sample t test with one variance unknown. American Statistician, 60(2), 163–166. https://doi.org/10.1198/000313006X108567

A Perturbation Technique for Sample Moment Matching in Kernel Density Estimation. (2005). Calcutta Statistical Association Bulletin. https://doi.org/10.1177/0008068320050510