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61. *Wang, C., Chen, M.-H., Wu, J., Yan, J., Zhang, Y., and Schifano, E. D. (2018): Online updating method with new
variables for big data streams. Canadian Journal of Statistics 46(1): 123–146.
62. *Bader, B., Yan, J., and Zhang, X. (2017): Automated selection of r for the r largest order statistics approach with
adjustment for sequential testing. Statistics and Computing 27(6): 1435–1451.
63. *Vaughan, G., Aseltine, R. H, Chen, K., and Yan, J. (2017): Stagewise estimating equations with grouped variables.
Biometrics 73(4): 1332–1342.
64. *Wang, Z., Jiang, Y., Wan, H., Yan, J., and Zhang, X. (2017): Detection and attribution of changes in extreme
temperatures at regional level. Journal of Climate 30(17): 7035–7047.
65. Xu, G., Chiou, S., Huang, C.-Y., Wang, M.-C., and Yan, J. (2017): Joint scale-change models for recurrent events
and failure time. Journal of the American Statistical Association 112: 794–805.
66. Olayivola, J. N., Adnerson, D. R., Jepeal, N., Aseltine, R. H., Pickett, C., Yan, J., and Zlateva, I. (2016): Electronic
consultations to improve the primary care-specialty care interface for cardiology in the medically underserved: A
cluster-randomized controlled trial. Annals of Family Medicine 14(2): 133–140.
67. Schifano, E. D., Wu, J., Wang, C., Yan, J. and Chen, M.-H. (2016): Online updating of statistical inference in the big
data setting. Technometrics 58(3): 393–403.
68. *Wang, C., Chen, M.-H., Schifano, E. D., Wu, J., and Yan, J. (2016): Statistical methods and computing for big data.
Statistics and Its Interfaces 9(4): 399–414.
69. *Wang, W., Chen, M.-H., Chiou, S., Lai, H.-C., Wang, X., Yan, J., and Zhang, Z. (2016): Onset of persistent Pseu-
domonas Aeruginosa infection in children with cystic fibrosis with interval censored data. BMC Medical Research
Methodology 16(122): 1–10.
70. Aseltine, R. H., Yan, J., Fleischman, S., Katz, M., and DeFrancesco M. (2015): Race and ethnic disparities in hospital
readmissions following vaginal and cesarean delivery. Obstetrics & Gynecology 126(5): 1040–1047.
71. Aseltine, R. H., Yan, J., Gruss, C. B., Wagner, C., and Katz, M. (2015): Connecticut hospital readmissions related to
chest pain and heart failure: Differences by race, ethnic, and payer. Connecticut Medicine 79(2): 69–76.
72. Chi, Z., Pozdnyakov, V., and Yan, J. (2015): On occupation time of Brownian motion. Statistics and Probability
Letters 97: 83–87.
73. *Chiou, S., Kang, S., and Yan, J. (2015): Semiparametric accelerated failure time modeling for clustered failure times
from stratified sampling. Journal of the American Statistical Association 110: 621–629.
74. *Chiou, S., Kang, S., and Yan, J. (2015): Rank-based estimating equations with general weight for accelerated failure
time models: An induced smoothing approach. Statistics in Medicine 34(9): 1495–1510.
75. Kojadinovic, I., Shang, H., and Yan, J. (2015): A class of goodness-of-fit tests for spatial extremes models based on
max-stable processes. Statistics and Its Interfaces 8(1): 45–62.
76. *Prates, M. O., Dey, D. K., Willig, M. R., and Yan, J. (2015): Transformed Gaussian Markov random fields and spatial
modeling. Spatial Statistics 14(C), 382–399.
77. *Shang, H., Yan, J., and Zhang, X. (2015): A two-step approach to model precipitation extremes in California based
on max-stable and marginal point processes. The Annals of Applied Statistics 9(1): 452–473.
78. *Chiou, S., Kang, S., Kim, J., and Yan, J. (2014): Marginal semiparametric multivariate accelerated failure time model
with generalized estimating equations. Lifetime Data Analysis 20(4): 599–618.
79. *Chiou, S., Kang, S., and Yan, J. (2014): Fitting accelerated failure time models in routine survival analysis. Journal
of Statistical Software 61(11): 1–23.
80. *Chiou, S., Kang, S., and Yan, J. (2014): Fast accelerated failure time modeling for case-cohort data. Statistics and
Computing 24(4): 559–568.
81. Pozdnyakov, V., Meyer, T., Wang, Y., and Yan, J. (2014): On modeling animal movement using Brownian motion with
measurement error. Ecology 95(2): 247–253.
82. *Wang, Z., Yan, J., and Zhang, X. (2014): Incorporating spatial dependence in regional frequency analysis. Water
Resources Research 50(12): 9570–9585.
83. Yan, J., Chen, Y., Lawrence-Apfel, K., Ortega, I. M., Pozdnyakov, V., Williams, S., and Meyer, T. (2014): A moving-
resting process with an embedded Brownian motion for animal movements. Population Ecology 56(2): 401–415.