Statistica Sinica

Volume 28,  Number 4, October 2018 

@corresponding author*
Data Missing Not at Random
  Foreword
Jae-Kwang Kim and Zhiliang Ying
 
1651
@ A mixed-effects estimating equation approach to nonignorable missing longitudinal data with refreshment samples
Xuan Bi and Annie Qu*
Supp doi:10.5705/ss.202015.0317
1653
@ Imputation-based adjusted score equations in generalized linear models with nonignorable missing covariate values
Fang Fang, Jiwei Zhao and Jun Shao*
  doi:10.5705/ss.202015.0437
1677
  Sensitivity analysis for unmeasured confounding in coarse structural nested mean models
Shu Yang* and Judith J. Lok
  doi:10.5705/ss.202016.0133
1703
@ Calibration and multiple robustness when data are missing not at random
Peisong Han*
  doi:10.5705/ss.202015.0408
1725
@ Sequential identification of nonignorable missing data mechanisms
Mauricio Sadinle* and Jerome P. Reiter
  doi:10.5705/ss.202016.0328
1741
@ Generalization of Heckman selection model to nonignorable nonresponse using call-back information
Baojiang Chen*, Pengfei Li and Jing Qin
Supp doi:10.5705/ss.202016.0300
1761
@ Rank-based estimating equation with non-ignorable missing responses via empirical likelihood
Huybrechts F. Bindele* and Yichuan Zhao
  doi:10.5705/ss.202016.0388
1787
@ Optimal design when outcome values are not missing at random
Kim May Lee*, Robin Mitra and Stefanie Biedermann
  doi:10.5705/ss.202016.0526
1821
  Bayesian small area models for three-way contingency tables with nonignorability
Namkyo Woo, Balgobin Nandram and Dalho Kim*
  doi:10.5705/ss.202016.0121
1839
@ Functional linear regression models for nonignorable missing scalar responses
Tengfei Li, Fengchang Xie, Xiangnan Feng, Joseph G. Ibrahim, Hongtu Zhu* and the Alzheimers Disease Neuroimaging Initiative
Supp doi:10.5705/ss.202016.0350
1867
@ Assessment of nonignoralbe log-linear models for an incomplete contingency table
Seongyong Kim and Daeyoung Kim*
Supp doi:10.5705/ss.202015.0472
1887
@ A robust calibration-assisted method for linear mixed effects model under cluster-specific nonignorable missingness
Yongchan Kwon, Jae Kwang Kim, Myunghee Cho Paik* and Hongsoo Kim
Supp doi:10.5705/ss.202016.0317
1907
@ Bayesian modeling and inference for nonignorably missing longitudinal binary response data with applications to HIV prevention trials
Jing Wu, Joseph G. Ibrahim*, Ming-Hui Chen, Elizabeth D. Schifano and Jeffrey D. Fisher
Supp doi:10.5705/ss.202016.0319
1929
  Semiparametric estimation with data missing not at random using an instrumental variable
BaoLuo Sun, Lan Liu, Wang Miao, Kathleen Wirth, James Robins and Eric J. Tchetgen Tchetgen*
Supp doi:10.5705/ss.202016.0324
1965
@ A mean score method for sensitivity analysis to departures from the missing at random assumption in randomised trials
Ian R. White*, James Carpenter and Nicholas J. Horton
Supp doi:10.5705/ss.202016.0308
1985
@ Propensity score matching analysis for causal effects with MNAR covariates
Bo Lu* and Robert Ashmead
  doi:10.5705/ss.202016.0320
2005
@ Empirical likelihood methods for complex surveys with data missing-by- design
Min Chen, Mary E. Thompson and Changbao Wu*
  doi:10.5705/ss.202016.0291
2027
  Identification and inference with nonignorable missing covariate data
Wang Miao* and Eric Tchetgen Tchetgen
Supp doi:10.5705/ss.202016.0322
2049
  Discrete choice models for nonmonotone nonignorable missing data: identification and inference
Eric J. Tchetgen Tchetgen*, Linbo Wang and BaoLuo Sun
Supp doi:10.5705/ss.202016.0325
2069
  Strategic binary choice models with partial observability
Mark David Nieman*
  doi:10.5705/ss.202016.0294
2089
@ Generalized method of moments for nonignorable missing data
Li Zhang, Cunjie Lin* and Yong Zhou
Supp doi:10.5705/ss.202016.0340
2107
@ Penalized pairwise pseudo likelihood for variable selection with nonignorable missing data
Jiwei Zhao*, Yang Yang and Yang Ning
Supp doi:10.5705/ss.202016.0312
2125
@ Estimation of area under the ROC curve under nonignorable verification bias
Wenbao Yu, Jae Kwang Kim and Taesung Park*
  doi:10.5705/ss.202016.0315
2149
@ Bayesian inference for nonresponse two-phase sampling
Yue Zhang, Henian Chen and Nanhua Zhang*
  doi:10.5705/ss.202017.0016
2167
@ Application of non-parametric empirical Bayes to treatment of non-response
Eitan Greenshtein* and Theodor Itskov
  doi:10.5705/ss.202016.0270
2189
In Memory of Peter Hall
  Foreword
Raymond J. Carroll, Qiwei Yao and Editors for this Special Issue
 
2209
@ Peter Gavin Hall
Terry Speed*
  doi:10.5705/ss.202018.0028
2215
@ Peter Gavin Hall -- A brief remembrance of the man and his work
Francisco J. Samaniego*
  doi:10.5705/ss.202017.0038
2237
  Peter Hall: My mentor, collaborator and friend
Peihua Qiu*
  doi:10.5705/ss.202017.0022
2249
@ Peter Hall on extremes: Research, teaching and supervision
Alan Welsh*
  doi:10.5705/ss.202017.0095
2261
@ Wavelet methods for erratic regression means in the presence of measurement error
Peter Hall, Spiridon Penev* and Jason Tran
Supp doi:10.5705/ss.202016.0393
2289
@ Semi-parametric prediction intervals in small areas when auxiliary data are measured with error
Gauri Datta, Aurore Delaigle*, Peter Gavin Hall and Lily Wang
Supp doi:10.5705/ss.202016.0416
2309
@ Clustering in general measurement error models
Ya Su, Jill Reedy and Raymond J. Carroll*
Supp doi:10.5705/ss.202017.0093
2337
@ Estimation of errors-in-variables partially linear additive models
Eun Ryung Lee, Kyunghee Han and Byeong U. Park*
Supp doi:10.5705/ss.202017.0101
2353
  Peter Hall's contribution to empirical likelihood
Jinyuan Chang*, Jianjun Guo and Cheng Yong Tang
  doi:10.5705/ss.202017.0059
2375
@ Hybrid combinations of parametric and empirical likelihoods
Nils Lid Hjort, Ian W. McKeague and Ingrid Van Keilegom*
Supp doi:10.5705/ss.202017.0291
2389
@ Empirical likelihood ratio tests for coefficients in high dimensional heteroscedastic linear models
Honglang Wang, Ping-Shou Zhong* and Yuehua Cui
Supp doi:10.5705/ss.202017.0041
2409
@ An outlyingness matrix for multivariate functional data classification
Wenlin Dai and Marc G. Genton*
Supp doi:10.5705/ss.202016.0537
2435
@ Adaptive functional linear regression via functional principal component analysis and block thresholding
T. Tony Cai*, Linjun Zhang and Harrison H. Zhou
Supp doi:10.5705/ss.202017.0099
2455
  Functional principal component analysis for derivatives of multivariate curves
Maria Grith*, Heiko Wagner,Wolfgang K. Hardle and Alois Kneip
Supp doi:10.5705/ss.202017.0199
2469
@ Singular additive models for function to function regression
Byeong U. Park, Chun-Jui Chen, Wenwen Tao and Hans-Georg Muller*
Supp doi:10.5705/ss.202016.0556
2497
@ Methodology and convergence rates for functional time series regression
Tung Pham and Victor M. Panaretos*
Supp doi:10.5705/ss.202016.0536
2521
@ Edgeworth correction for the largest eigenvalue in a spiked PCA model
Jeha Yang and Iain M. Johnstone*
Supp doi:10.5705/ss.202017.0296
2541
  Calibrated percentile double bootstrap for robust linear regression inference
Daniel McCarthy, Kai Zhang*, Lawrence D. Brown, Richard Berk, Andreas Buja, Edward I. George and Linda Zhao
  doi:10.5705/ss.202016.0546
2565
  Edgeworth expansions for a class of spectral density estimators and their applications to interval estimation
Arindam Chatterjee* and Soumendra N. Lahiri
Supp doi:10.5705/ss.202017.0121
2591
  A bootstrap method for constructing pointwise and uniform confidence bands for conditional quantile functions
Joel L. Horowitz* and Anand Krishnamurthy
Supp doi:10.5705/ss.202017.0013
2609
@ Partial consistency with sparse incidental parameters
Jianqing Fan, Runlong Tang* and Xiaofeng Shi
Supp doi:10.5705/ss.202017.0027
2633
@ Applications of Peter Hall's martingale limit theory to estimating and testing high dimensional covariance matrices
Danning Li, Lingzhou Xue and Hui Zou*
Supp doi:10.5705/ss.202017.0060
2657
@ High-dimensional two-sample covariance matrix testing via super-diagonals
Jing He and Song Xi Chen*
Supp doi:10.5705/ss.202017.0213
2671
@ Estimating a discrete log-concave distribution in higher dimensions
Hanna Jankowski* and Yan Hua Tian
Supp doi:10.5705/ss.202017.0344
2697
@ Asymptotic behavior of cox's partial likelihood and its application to variable selection
Runze Li*, Jian-Jian Ren, Guangren Yang and Ye Yu
Supp doi:10.5705/ss.202016.0401
2713
@ Data sharpening in local regression guided by global constraint
W. John Braun*, X. Joan Hu and Xiuli Kang
Supp doi:10.5705/ss.202017.0056
2733
@ Bias reduction for nonparametric and semiparametric regression models
Ming-Yen Cheng*, Tao Huang, Peng Liu and Heng Peng
Supp doi:10.5705/ss.202017.0058
2749
  Nonlinear regression estimation using subset-based kernel principal components
Yuan Ke, Degui Li* and Qiwei Yao
  doi:10.5705/ss.202016.0369
2771
  Optimal model averaging of varying coefficient models
Cong Li, Qi Li, Jeffrey S. Racine* and Daiqiang Zhang
Supp doi:10.5705/ss.202017.0034
2795
  Empirical Fourier methods for interval censored data
Peter G. Hall, John Braun* and Thierry Duchesne
Supp doi:10.5705/ss.202017.0057
2811
@ On p-values
Laurie Davies*
  doi:10.5705/ss.202016.0507
2823
@ Kernel-based adaptive randomization toward balance in continuous and discrete covariates
Fei Jiang, Yanyuan Ma* and Guosheng Yin
Supp doi:10.5705/ss.202016.0538
2841
@ Tests for tar models vs. Star models--A separate family of hypotheses approach
Zhaoxing Gao*, Shiqing Ling and Howell Tong
Supp doi:10.5705/ss.202016.0497
2857
@ Likelihood ratio Haar variance stabilization and normalization for Poisson and other non-Gaussian noise removal
Piotr Fryzlewicz*
Supp doi:10.5705/ss.202017.0029
2885
@ RFMS method for credit scoring based on bank card transaction data
Danyang Huang, Jing Zhou* and Hansheng Wang
  doi:10.5705/ss.202017.0043
2903

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