Forthcoming Issue
The following papers are expected to appear in
Volume 29, Number 4, October 2019
corresponding author*
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Discussion |
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1. SS-2018-0076 [Supp] |
doi:10.5705/ss.202018.0076 |
Entropy learning for dynamic treatment regimes
Binyan Jiang, Rui Song, Jialiang Li* and Donglin Zeng |
2. SS-2019-0015 |
doi:10.5705/ss.202019.0015 |
Discussion of ˇ§Entropy learning for dynamic treatment regimesˇ¨ by Jiang Song, Li and Zeng
Wenbin Lu* |
3. SS-2019-0035 |
doi:10.5705/ss.202019.0035 |
Discussion on ˇ§Entropy learning for dynamic treatment regimesˇ¨
Xin He, Shirong Xu and Junhui Wang* |
4. SS-2019-0034 |
doi:10.5705/ss.202019.0034 |
Discussion on ˇ§Entropy learning for dynamic treatment regimesˇ¨
Min Qian* and Bin Cheng |
5. SS-2019-0062 |
doi:10.5705/ss.202019.0062 |
Comment on ˇ§Entropy learning for dynamic treatment regimesˇ¨ by Binyan Jiang, Rui Song, et al.
Hongxiang Qiu*, Alex Luedtke and Mark van der Laan |
6. SS-2019-0071 |
doi:10.5705/ss.202019.0071 |
On regression tables for policy learning: comment on a paper by Jiang, Song, Li and Zeng
Stefan Wager* |
7. SS-2019-0089 |
doi:10.5705/ss.202019.0089 |
Discussion of ˇ§Entropy learning for dynamic treatment regimesˇ¨
Yichi Zhang and Eric B. Laber* |
8. SS-2019-0115 |
doi:10.5705/ss.202019.0115 |
Comment: Entropy learning for dynamic treatment regimes
Nathan Kallus* |
9. SS-2019-0171 |
doi:10.5705/ss.202019.0171 |
Rejoinder for ˇ§Entropy learning for dynamic treatment regimesˇ¨
Binyan Jiang, Rui Song, Jialiang Li* and Donglin Zeng |
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General |
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1. SS-2017-0008 [Supp] |
doi:10.5705/ss.202017.0008 |
Smoothed full-scale approximation of Gaussian process models for computation of large spatial datasets
Bohai Zhang*, Huiyan Sang and Jianhua Z. Huang |
2. SS-2017-0106 [Supp] |
doi:10.5705/ss.202017.0106 |
Strong laws for randomly weighted sums of random variables and applications in the bootstrap and random design regression
Pingyan Chen, Tao Zhang and Soo Hak Sung* |
3. SS-2017-0288 [Supp] |
doi:10.5705/ss.202017.0288 |
Sufficient dimension reduction under dimension-reduction-based imputation with predictors missing at random
Xiaojie Yang and Qihua Wang* |
4. SS-2017-0236 |
doi:10.5705/ss.202017.0236 |
A test for equality of two distributions via integrating characteristic functions
Yiming Liu, Zhi Liu* and Wang Zhou |
5. SS-2017-0341 [Supp] |
doi:10.5705/ss.202017.0341 |
Statistical inference for structurally changed threshold autoregressive models
Zhaoxing Gao* and Shiqing Ling |
6. SS-2017-0466 [Supp] |
doi:10.5705/ss.202017.0466 |
The bias mapping of the yule-walker estimator is a contraction
Philip A. Ernst* and Paul Shaman |
7. SS-2017-0326 [Supp] |
doi:10.5705/ss.202017.0326 |
Semiparametric transformation models with multilevel random effects for correlated disease onset in families
Baosheng Liang, Yuanjia Wang* and Donglin Zeng |
8. SS-2017-0179 [Supp] |
doi:10.5705/ss.202017.0179 |
Robust subgroup identification
Yingying Zhang, Huixia Judy Wang and Zhongyi Zhu* |
9. SS-2016-0459 [Supp] |
doi:10.5705/ss.202016.0459 |
Two-sample functional linear models
Wenchao Xu, Riquan Zhang* and Hua Liang |
10. SS-2016-0114 [Supp] |
doi:10.5705/ss.202016.0114 |
Imprinting and maternal effect detection using partial likelihood based on discordant sibpair data
Fangyuan Zhang, Abbas Khalili and Shili Lin* |
11. SS-2017-0089 [Supp] |
doi:10.5705/ss.202017.0089 |
Pseudo value method for ultra high-dimensional semiparametric models with lifetime data
Tony Sit*, Yue Xing, Yongze Xu and Minggao Gu |
12. SS-2016-0345 [Supp] |
doi:10.5705/ss.202016.0345 |
On estimation of partially linear varying-coefficient transformation models with censored data
Bo Li, Baosheng Liang, Xingwei Tong and Jianguo Sun* |
13. SS-2017-0153 [Supp] |
doi:10.5705/ss.202017.0153 |
Tensor generalized estimating equations for longitudinal imaging analysis
Xiang Zhang, Lexin Li, Hua Zhou*, Yeqing Zhou, Dinggang Shen, and ADNI |
14. SS-2017-0505 [Supp] |
doi:10.5705/ss.202017.0505 |
FMEM: Functional mixed effects models for longitudinal functional responses
Hongtu Zhu*, Kehui Chen, Xinchao Luo, Ying Yuan and Jane-Ling Wang |
15. SS-2017-0126 |
doi:10.5705/ss.202017.0126 |
Multiply robust nonparametric multiple imputation for the treatment of missing data
Sixia Chen and David Haziza* |
16. SS-2017-0208 [Supp] |
doi:10.5705/ss.202017.0208 |
A simple method to construct confidence bands in functional linear regression
Masaaki Imaizumi* and Kengo Kato |
17. SS-2017-0175 [Supp] |
doi:10.5705/ss.202017.0175 |
Nonparametric inference for Markov processes with missing absorbing state
Giorgos Bakoyannis*, Ying Zhang and Constantin T. Yiannoutsos |
18. SS-2017-0298 [Supp] |
doi:10.5705/ss.202017.0298 |
Marginal screening for high-dimensional predictors of survival outcomes
Tzu-Jung Huang*, Ian W. McKeague and Min Qian |
19. SS-2016-0348 |
doi:10.5705/ss.202016.0348 |
Maximum partial-rank correlation estimation for left-truncated and right-censored survival data
Shao-Hsuan Wang and Chin-Tsang Chiang* |
20. SS-2017-0354 [Supp] |
doi:10.5705/ss.202017.0354 |
An adaptive test on high-dimensional parameters in generalized linear models
Chong Wu*, Gongjun Xu and Wei Pan |
21. SS-2017-0332 |
doi:10.5705/ss.202017.0332 |
Design admissibility, invariance and optimality in multiresponse linear models
Xin Liu and Rong-Xian Yue* |
22. SS-2017-0217 [Supp] |
doi:10.5705/ss.202017.0217 |
A matrix-free method for spatial-temporal Gaussian state-space models
Debashis Mondal* and Chunxiao Wang |
23. SS-2018-0233 [Supp] |
doi:10.5705/ss.202018.0233 |
Monotone nonparametric regression for functional/longitudinal data
Ziqi Chen, Qibing Gao, Bo Fu and Hongtu Zhu* |