content

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