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## Publications

Publications (127)

Rubin's variance estimator of the multiple imputation estimator for a domain mean is not asymptotically unbiased. Kim et al. derived the closed-form bias for Rubin's variance estimator. In addition, they proposed an asymptotically unbiased variance estimator for the multiple imputation estimator when the imputed values can be written as a linear fu...

Empirical likelihood is widely used in many statistical problems. In this article, we provide a review of the empirical likelihood method, due to its significant development in recent years. Since the introduction of empirical likelihood, variants of empirical likelihood have been proposed, and the applications of empirical likelihood in high dimen...

Empirical likelihood is a popular nonparametric statistical tool that does not require any distributional assumptions. In this paper, we explore the possibility of conducting variable selection via Bayesian empirical likelihood. We show theoretically that when the prior distribution satisfies certain mild conditions, the corresponding Bayesian empi...

Variance estimation is fundamental in the statistical inference. Due to the nonlinearity of the variance estimator, Lin et al. [Jackknife empirical likelihood for the error variance in linear models. J Nonparametr Stat. 2017;29:151-166.] proposed the jackknife empirical likelihood method for the error variance in a linear regression model. However,...

In survival analysis and reliability theory, the mean past lifetime (MPL), arises in situations where the mean time elapsed since the failure of a component T, given that it has failed before time t, is of interest. For inference on the MPL function, some procedures have been proposed in the literature for the MPL function's estimator. In this pape...

CALL FOR BOOK CHAPTERS,
Title: Data Analytics for Management, Banking and Finance.
Over the past few decades, the world has experienced many social, economic and evenhealth upheavals. On the financial level, we have experienced the two worst global financialcrises since the Great Depression in the 1930s. At the heart of this turbulence, contagions...

In the absence of reliable information about transmission mechanisms for emerging infectious diseases, simple phenomenological models could provide a starting point to assess the potential outcomes of unfolding public health emergencies, particularly when the epidemiological characteristics of the disease are poorly understood or subject to substan...

Disease status can naturally be classified into three or more ordinal stages rather than just being binary stages. Many works have been done for the estimation and inference procedure regarding three ordinal disease stages, which are non-disease, early disease and full disease stages. The early disease stage can be very important for therapeutic in...

Probability weighted moments (PWMs) are a generalization of the usual moments of a probability distribution. In this paper, the jackknife empirical likelihood (JEL), the adjusted JEL (AJEL), the transformed JEL, which combines the merits of jackknife and transformed empirical likelihoods (TJEL), the transformed adjusted JEL (TAJEL), the mean jackkn...

Over the last years, artificial intelligence (AI) models have become so complex that understanding them has raised the question about their interpretability. The terms interpretability and explainability have been used by researchers interchangeably. These two terms sound like very closely related, but according to some works one has to distinguish...

In this paper, we investigate the varying coefficient models for spatial data distributed over two-dimensional domains. First, the univariate components and the geographical component in the model are approximated via univariate polynomial splines and bivariate penalized splines over triangulation, respectively. The spline estimators of the univari...

This paper focuses on comparing two means and finding a confidence interval for the difference of two means with right-censored data using the empirical likelihood method combined with the independent and identically distributed random functions representation. In the literature, some early researchers proposed empirical likelihood-based confidence...

Background: Multiple sclerosis (MS) detrimentally affects cognition and quality of life (QOL). Interventions that can improve cognitive deficit and QOL in people with MS are desired. This pilot study investigated the possible effects of vibration training on improving cognition and QOL in people with MS.
Methods: Eighteen adults with MS were rando...

One effective way to conduct statistical disclosure control is to use scrambled responses. Scrambled responses can be generated by using a controlled random device. In this paper, we propose using the sample empirical likelihood approach to conduct statistical inference under complex survey design with scrambled responses. Specifically, we propose...

In this book chapter, we provide a general overview on the Bayesian experimental design of various statistical models in the recent years. The Bayesian optimal designs incorporate the prior information and uncertainties of the models by using various utility functions, which describe various aims of the experiments. Although there are difficulties...

This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for healt...

The mean residual life (MRL) function for a given random variable T is the expected remaining lifetime of T after a fixed time point t. It is of great interest in survival analysis, reliability, actuarial applications , duration modelling, etc. Liang, Shen, and He ['Likelihood Ratio Inference for Mean Residual Life of Length-biased Random Variable'...

Generalized additive partially linear models enjoy the simplicity of GLMs and the flexibility of GAMs because they combine both parametric and nonparametric components. Based on spline-backfitted kernel estimator, we propose empirical likelihood (EL)-based pointwise confidence intervals and simultaneous confidence bands (SCBs) for the nonparametric...

In constructing a confidence interval for the mean difference of two independent populations, we may encounter the problem of having a low coverage probability when there are many zeros in the data, and the non-zero values are highly positively skewed. The violation of the normality assumption makes parametric methods inefficient in such cases. In...

The Pietra ratio (Pietra index) is also known as the Robin Hood index or Schutz coefficient (Ricci-Schutz index). It is a measure of statistical heterogeneity in positive random variables. In this paper, we propose the jackknife empirical likelihood (JEL), the adjusted JEL, the extended JEL, and the balanced adjusted JEL methods, for interval estim...

The submission deadline is December 15, 2020 and the expected publication date is June 15, 2021. The details of the special issue can be found from the link https://think.taylorandfrancis.com/special_issues/applied-statistics-covid-19-data/
The guest editors solicit applied papers fitting broadly under our special issue title: Statistical Perspect...

The submission deadline is September 30, 2020 and the expected publication date is March 30, 2021.
The details of the special issue can be found from the link https://think.taylorandfrancis.com/special_issues/statistical-big-data/.
The guest editors solicit results mainly concerning recent advances and challenges in both the theory and applicati...

Owen (1988, 1990) proposed an innovative empirical likelihood (EL) approach for the confidence interval of mean based on the complete data. EL is a pure nonparametric approach, which has been applied in numerous research fields due to the excellent performance for the small sample compared to other existing methods. It is preferable to other parame...

Environmental surveillance can be used for monitoring enteric disease in a population by detecting pathogens, shed by infected people, in sewage. Detection of pathogens depends on many factors: infection rates and shedding in the population, pathogen fate in the sewerage network, and also sampling sites, sample size, and assay sensitivity. This com...

This edited collection discusses the emerging topics in statistical modeling for biomedical research. Leading experts in the frontiers of biostatistics and biomedical research discuss the statistical procedures, useful methods, and their novel applications in biostatistics research. Interdisciplinary in scope, the volume as a whole reflects the lat...

Features the contributions of leading experts in the statistical modeling and analysis in biostatistics and bioinformatics; Includes a foundational overview of modeling in biomedical research to guide the reader in learning efficiently; Covers new advances in machine learning, GWAS data analysis, next generation sequence analysis, and survival anal...

Empirical likelihood is a very powerful nonparametric tool that does not require any distributional assumptions. Lazar (2003) showed that in Bayesian inference, if one replaces the usual likelihood with the empirical likelihood, then posterior inference is still valid when the functional of interest is a smooth function of the posterior mean. Howev...

The categorical Gini correlation is an alternative measure of
dependence between a categorical and numerical variables, which characterizes the independence of the variables. A nonparametric test for the equality of K distributions has been developed based on the categorical Gini correlation. By applying the jackknife empirical likelihood approach...

In many applications, parameters of interest are estimated by solving some non-smooth estimating equations with U-statistic structure. Jackknife empirical likelihood (JEL) approach can solve this problem efficiently by reducing the computation complexity of the empirical likelihood (EL) method. However, as EL, JEL suffers the sensitivity problem to...

In many applications, parameters of interest are estimated by solving some non-smooth estimating equations with $U$-statistic structure. Jackknife empirical likelihood (JEL) approach can solve this problem efficiently by reducing the computation complexity of the empirical likelihood (EL) method. However, as EL, JEL suffers the sensitivity problem...

The Gini index has been widely used as a measure of income (or wealth) inequality in social sciences. To construct a confidence interval for the difference of two Gini indices from the paired samples, Wang and Zhao (2016) used a profile jackknife empirical likelihood after maximization over a nuisance parameter and established Wilks' theorem. Howev...

In this paper, we consider inference of the stress-strength parameter, $R$, based on two independent Type-II censored samples from exponentiated Fr\'echet populations with different index parameters. The maximum likelihood and uniformly minimum variance unbiased estimators, exact and asymptotic confidence intervals and hypotheses testing for $R$ ar...

Empirical likelihood is a very powerful nonparametric tool that does not require any distributional assumptions. Lazar (2003) showed that, if you replace the usual likelihood component in the Bayesian posterior likelihood with the empirical likelihood, then posterior inference is still valid when the functional of interest is a smooth function of t...

In many statistical analysis, data may consist of excess zero values and the non-zero values are highly positively skewed. Confidence intervals based on a normal approximation for such zero-inflated data may have low coverage probabilities. An empirical likelihood (EL) and adjusted empirical likelihood methods are proposed to construct a non-parame...

The current penalized regression methods for selecting predictor variables and estimating the associated regression coefficients in the sparse Cox model are mainly based on partial likelihood. In this paper, a bias-corrected empirical likelihood method is proposed for the sparse Cox model in conjunction with appropriate penalty functions when the d...

The semi-parametric transformation models under length-biased sampling are considered. The well-known proportional hazards model and proportional odds model are special cases of the semi-parametric transformation models. Empirical likelihood and adjusted empirical likelihood inferences for semi-parametric transformation models with length-biased sa...

Coefficients of skewness and kurtosis provide convenient measures for describing the shape of a distribution based on a sample of independent observations. In this paper, we propose jackknife empirical likelihood (JEL) confidence intervals for the skewness and kurtosis coefficients, proving that the limiting distribution of the JEL ratio is a stand...

Accelerated failure time (AFT) model is a useful semi-parametric model under right
censoring, which is an alternative to the commonly used proportional hazards model.
Making inference for the AFT model has attracted considerable attention.
However, it is difficult to compute the estimators of regression parameters due to
the lack of smoothness for...

International Conference on Physics, Mathematics and Statistics (ICPMS2018) was successfully held in Shanghai, China during May 12 to 14, 2018. The conference was an annual forum for researchers and application developers in the area of Physics, Mathematics and Statistics. This conference proceeding included 139 accepted articles selected from 347...

During statistical analysis of clinic data, missing data is a common challenge. Incomplete datasets can occur via different means, such as mishandling of samples, low signal-to-noise ratio, measurement error, non-responses to questions, or aberrant value deletion. Missing data causes severe problems in statistical analysis and leads to invalid conc...

The reverse-time hazard was routinely evaluated or modeled under the context of right truncation. However, this quantity does not have a natural interpretation. Based on the relation between the reverse-time and forward-time hazards, we developed the nonparametric inference for the forward-time hazard. We studied a family of weighted tests for comp...

Left truncation and right truncation coexist in a truncated sample. Earlier researches focused on left truncation. Lagakos et al. (Biometrika 75:515–523, 1988) proposed to transform right truncated data to left truncated data and then apply the methods developed for left truncation. Interpretation of survival quantities, such as the hazard rate fun...

In this paper, a general regression model with responses missing at random is considered. From an imputed rank-based objective function, a rank-based estimator is derived and its asymptotic distribution is established under mild conditions. Inference based on the normal approximation approach results in under coverage or over coverage issues. In or...

This book is mainly comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers mainly from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of bios...

The Gini correlation plays an important role in measuring dependence of random variables with heavy tailed distributions, whose properties are a mixture of Pearson's and Spearman's correlations. Due to the structure of this dependence measure, there are two Gini correlations between each pair of random variables, which are not equal in general. Bot...

Next-generation sequencing has become a powerful tool for gene expression analysis with the development of high-throughput techniques. Discriminating which type of diseases a new sample belongs to is a fundamental issue in medical and biological studies. Different from continuous microarray data, next-generation sequencing reads are mapped onto the...

This paper presents simple weighted and fully augmented weighted estimators for the additive hazards model with missing covariates when they are missing at random. The additive hazards model estimates the difference in hazards and has an intuitive biological interpretation. The proposed weighted estimators for the additive hazards model use incompl...

This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of...

The volume under a surface (VUS) is an effective measure for evaluating the discriminating power of a diagnostic test with three ordinal diagnostic groups. In this paper, we investigate the difference of two correlated VUS’s to compare two treatments for discrimination of three-class classification data. A jackknife empirical likelihood (JEL) proce...

The one-sample quantile difference measure, which includes the interquartile range (IQR) of a given distribution, plays an important role in statistical sciences and econometrics. A jackknife empirical likelihood (JEL) method for the quantile difference is proposed using a novel smoothed nonparametric estimating equation. The asymptotic chi-square...

The bivariate survival function plays an important role in multivariate survival analysis. Using the idea of influence functions, we develop empirical likelihood confidence intervals for the bivariate survival function in the presence of univariate censoring. It is shown that the empirical log-likelihood ratio has an asymptotic standard chi-squared...

In this paper, a general regression model with responses missing not at random is considered. From a rank-based estimating equation, a rank-based estimator of the regression parameter is derived. Based on this estimator's asymptotic normality property, a consistent sandwich estimator of its corresponding asymptotic covariance matrix is obtained. In...

For a continuous scale biomarker of binary disease status, the Youden index is a frequently used measurement of diagnostic accuracy in context of the receiver operating characteristic curve and provides an optimal threshold for making diagnosis. The majority of existing inference methods for the Youden index are either parametric or bootstrap based...

Variance estimation is a fundamental yet important problem in statistical modelling. In this paper, we propose jackknife empirical likelihood (JEL) methods for the error variance in a linear regression model. We prove that the JEL ratio converges to the standard chi-squared distribution. The asymptotic chi-squared properties for the adjusted JEL an...

The receiver operating characteristic (ROC) curve is a well-known measure of the performance of a classification method. Interest may only pertain to a specific region of the curve and, in this case, the partial area under the ROC curve (pAUC) provides a useful summary measure. Related measures such as the ordinal dominance curve (ODC) and the part...

In this paper, we propose a smoothed estimating equation for the difference of quantiles with two samples. Using the jackknife pseudo-sample technique for the estimating equation, we propose the jackknife empirical likelihood (JEL) ratio and establish the Wilk’s theorem. Due to avoiding estimating link variables, the simulation studies demonstrate...

The focus of this paper is to derive the jackknife empirical likelihood for the difference of two Gini indices. For independent data we propose a novel U-statistic, which allows direct utilization of the jackknife empirical likelihood without involving a nuisance parameter. For paired data we established Wilks’ theorem for the profile likelihood af...

In statistics mean absolute deviation plays an important role in measuring spread of a data. In this paper, we focus on using the jackknife, the adjusted and the extended jackknife empirical likelihood methods to construct confidence intervals for the mean absolute deviation of a random variable. The empirical log-likelihood ratio statistic is deri...

In this paper, we apply the empirical likelihood method to make inference on the bivariate survival function of paired failure times by estimating the survival function of censored time with the Kaplan-Meier estimator. Adjusted empirical likelihood (AEL) confidence intervals for the bivariate survival function are developed. We conduct a simulation...

Kendall and Gehan estimating functions are commonly used to estimate the regression parameter in accelerated failure time model with censored observations in survival analysis. In this paper, we apply the jackknife empirical likelihood method to overcome the computation difficulty about interval estimation. A Wilks’ theorem of jackknife empirical l...

A class of linear transformation models with censored data was proposed as a generalization of Cox models in survival analysis. This paper develops inference procedure for regression parameters based on jackknife empirical likelihood approach. We can show that the limiting variance is not necessary to estimate and the Wilk’s theorem can be obtained...

In this paper, we apply smoothed jackknife empirical likelihood (JEL) method to construct confidence intervals for the receiver operating characteristic (ROC) curve with missing data. After using hot deck imputation, we generate pseudo-jackknife sample to develop jackknife empirical likelihood. Comparing to traditional empirical likelihood method,...

The accelerated failure time (AFT) model, also called censored linear regression has played a central role in survival analysis. Motivated by (Zhao, Stat Probab Lett 81:603bab, 2011), we make an empirical likelihood (EL) inference for the model using the monotone censored Kendall’s rank-estimating equation. The limiting distribution of the EL ratio...

For the general stochastic regression analysis of complete data, Bindele and Abebe [Bounded influence nonlinear signed-rank regression. Can J Stat. 2012;40(1):172–189. Available from: http://dx.doi.org/10.1002/cjs.10134 ] proposed the signed-rank (SR) estimator. However, there exists an over-coverage problem for the confidence intervals of the regr...

In this paper, using a smoothed empirical likelihood method, we investigate the difference of quantiles in the two independent samples and construct the confidence intervals. We prove that the limiting distribution of the empirical log-likelihood ratio is a chi-squared distribution like Shen and He (2007). In the simulation studies, in terms of cov...

Disruptive network communication entails transient network connectivity, asymmetric links, and unstable nodes, which pose severe challenges to data collection in sensor networks. Erasure coding can be applied to mitigate the dependency of feedback in such a disruptive network condition, improving data collection. However, the collaborative data col...

It is of interest that researchers study competing risks in which subjects may fail from any one of k causes. Comparing any two competing risks with covariate effects is very important in medical studies. In this paper, we develop tests for comparing cause-specific hazard rates and cumulative incidence functions at specified covariate levels under...

For regression analysis of interval-censored failure time data, Z. Zhang et al. [Can. J. Stat. 33, No. 1, 61–70 (2005; Zbl 1063.62061)] proposed an estimating equation approach to fit linear transformation models. We develop two empirical likelihood (EL) inference approaches for the regression parameters based on generalized estimating equations. T...

For the comparison of two diagnostic markers at a flexible specificity, people apply the difference of two correlated receiver operating characteristic (ROC) curves to identify the diagnostic test with stronger discrimination ability. In this paper, we employ the jackknife empirical likelihood (JEL) method to construct confidence intervals for the...

The receiver operating characteristic (ROC) curve is one of the most commonly used methods to compare the diagnostic performance of two or more laboratory or diagnostic tests. In this paper, we propose semi-empirical likelihood based confidence intervals for ROC curves of two populations, where one population is parametric and the other one is non-...

Imbalanced data is a common and serious problem in many biomedical classification tasks. It causes a bias on the training of classifiers and results in lower accuracy of minority classes prediction. This problem has attracted a lot of research interests in the past decade. Unfortunately, most research efforts only concentrate on 2-class problems. I...

The clinical trial, a prospective study to evaluate the effect of interventions in humans under prespecified conditions, is a standard and integral part of modern medicine. Many adaptive and sequential approaches have been proposed for use in clinical trials to allow adaptations or modifications to aspects of a trial after its initiation without un...

We consider the (profile) empirical likelihood inferences for the regression parameter (and its any sub-component) in the semiparametric additive isotonic regression model where each additive nonparametric component is assumed to be a monotone function. In theory, we show that the empirical log-likelihood ratio for the regression parameters weakly...