Jianguo Sun

University of Missouri | Mizzou ·  Department of Statistics

Estimation of compiler causal treatment effects has been discussed by many authors under different situations but only limited literature exists for interval-censored failure time data, which often occur in many areas such as longitudinal or periodical follow-up studies. Particularly it does not seem to exist a method that can deal with informative...

The accelerated hazards model is one of the most commonly used models for regression analysis of failure time data and this is especially the case when, for example, the hazard functions may have monotonicity property. Correspondingly a large literature has been established for its estimation or inference when right-censored data are observed. Alth...

Background Failure time data frequently occur in many medical studies and often accompany with various types of censoring. In some applications, left truncation may occur and can induce biased sampling, which makes the practical data analysis become more complicated. The existing analysis methods for left-truncated data have some limitations in tha...

Length-biased data occur often in many scientific fields, including clinical trials, epidemiology surveys and genome-wide association studies, and many methods have been proposed for their analysis under various situations. In this article, we consider the situation where one faces length-biased and partly interval-censored failure time data under...

Misclassified current status data arises if each study subject can only be observed once and the observation status is determined by a diagnostic test with imperfect sensitivity and specificity. For the situation, another issue that may occur is that the observation time may be correlated with the interested failure time, which is often referred to...

The case-cohort design was developed to reduce costs when disease incidence is low and covariates are difficult to obtain. However, most of the existing methods are for right-censored data and there exists only limited research on interval-censored data, especially on regression analysis of bivariate interval-censored data. Interval-censored failur...

We discuss regression analysis of current status data with the additive hazards model when the failure status may suffer misclassification. Such data occur commonly in many scientific fields involving the diagnosis test with imperfect sensitivity and specificity. In particular, we consider the situation where the sensitivity and specificity are kno...

This paper discusses the goodness‐of‐fit test of semiparametric copula models when one faces bivariate interval‐censored failure time data, which often occur in many areas including epidemiological and medical studies as well as social science experiments. For the problem, three test statistics or procedures are proposed, two based on the pseudo in...

In this paper, we discuss regression analysis of bivariate interval-censored failure time data that often occur in biomedical and epidemiological studies. To solve this problem, we propose a kind of general and flexible copula-based semiparametric partly linear additive hazards models that can allow for both time-dependent covariates and possible n...

Estimation of causal treatment effects has attracted a great deal of interest in many areas including social, biological and health science, and for this, instrumental variable (IV) has become a commonly used tool in the presence of unmeasured confounding. In particular, many IV methods have been developed for right-censored time-to-event outcomes....

Linear transformation models have been one type of models commonly used for regression analysis of failure time data partly due to their flexibility. More recently they have been generalised to the case where there may exist a cured subgroup or the censoring may be informative. In this paper, we consider a more complicated and general situation whe...

Background: Failure time data occur frequently in many medical studies and often accompany with various types of censoring. In some applications, left truncation may occur and can induce biased sampling, which makes the practical data analysis become more complicated. The existing analysis methods for left-truncated data has some limitations in tha...

Panel count data consist of the numbers of event occurrences between two consecutive observation times and are prevalent in many areas. Correspondingly a bulk of literature has been developed for the analysis of panel count data with time-independent or time-dependent covariates but assuming time-invariant covariate effects. However, the time-invar...

Regression analysis of interval-censored failure time data has recently attracted a great deal of attention partly due to their increasing occurrences in many fields. In this paper, we discuss a type of such data, multivariate current status data, where in addition to the complex interval data structure, one also faces dependent or informative cens...

Semi-parametric transformation models provide a general and flexible class of models for regression analysis of failure time data and many methods have been developed for their estimation. In particular, they include the proportional hazards and proportional odds models as special cases. In this paper, we discuss the situation where one observes le...

The standard Cox model is perhaps the most commonly used model for regression analysis of failure time data but it has some limitations such as the assumption on linear covariate effects. To relax this, the nonparametric additive Cox model, which allows for nonlinear covariate effects, is often employed, and this paper will discuss variable selecti...

This paper discusses the fitting of the proportional hazards model to interval-censored failure time data with missing covariates. Many authors have discussed the problem when complete covariate information is available or the missing is completely at random. In contrast to this, we will focus on the situation where the missing is at random. For th...

Variable selection is needed and performed in almost every field and a large literature on it has been established, especially under the context of linear models or for complete data. Many authors have also investigated the variable selection problem for incomplete data such as right-censored failure time data. In this paper, we discuss variable se...

The prevalence of lung cancer induced by cigarette smoking has increased over time. Long noncoding (lnc) RNAs, regulatory factors that play a role in human diseases, are commonly dysregulated in lung cancer. Cigarette smoking is closely related to changes in lncRNA expression, which can affect lung cancer. Herein, we assess the mechanism of lung ca...

Misclassified current status data arise when the failure time of interest is observed or known only to be either smaller or larger than an observation time rather than observed exactly, and the failure status is examined by a diagnostic test with testing error. Such data commonly occur in various scientific fields, including clinical trials, demogr...

Cloud computing provides enterprises and individuals with unlimited computing resources and expandable storage space. However, data leakage occurs frequently due to the lack of protection measures in the cloud storage environment. Consequently, how to protect data security in the cloud has become a critical issue. Attribute-based encryption (ABE) i...

The proportional mean residual life model has been discussed by many authors and provides a useful alternative to the commonly used proportional hazards model for regression analysis of failure time data. In this paper, we discuss the estimation of the model when there exist internal and longitudinal covariates or variables in addition to the failu...

Variable selection has recently attracted a great deal of attention and in particular, a couple of methods have been proposed for general interval-censored failure time data or the interval-censored data arising from case-cohort studies. However, all of them have some limitations or apply only to limited situations. Corresponding to these, a new, m...

Variable selection is often needed in many fields and has been discussed by many authors in various situations. This is especially the case under linear models and when one observes complete data. Among others, one common situation where variable selection is required is to identify important risk factors from a large number of covariates. In this...

We consider efficient estimation of flexible transformation models with interval‐censored data. To reduce the dimension of semiparametric models, the unknown monotone function is approximated via a monotone B‐spline. A penalization technique is used to provide computationally efficient estimation of all parameters. To accomplish model fitting and i...

Affected by the complex environment and the destruction of communication infrastructure in the disaster-stricken area, it has brought great challenges to the search and rescue team. The use of small unmanned aerial vehicles (UAVs) for search tasks can minimize casualties. Therefore, in order to avoid any possible collision and search for unknown ta...

The performance of scene classification for remote sensing images based on deep neural networks is limited by the number of labeled data. To alleviate this problem, a variety of methods have been proposed to apply semi-supervised learning to exploit both labeled and unlabeled samples for training classifiers, but most of them still require a certai...

Panel count data arise when the study subjects who may experience certain recurrent events are only observed intermittently at discrete examination times. For the situation, in addition to the underlying recurrent event process of interest, there usually exist two other nuisance processes, the observation and follow-up processes, which may be corre...

Regression analysis of multivariate interval-censored failure time data has been discussed by many authors ¹⁻⁶ . For most of the existing methods, however, one limitation is that they only apply to the situation where the censoring is non-informative or the failure time of interest is independent of the censoring mechanism. It is apparent that this...

For the underwater acoustic targets recognition, it is a challenging task to provide good classification accuracy for underwater acoustic target using radiated acoustic signals. Generally, due to the complex and changeable underwater environment, when the difference between the two types of targets is not large in some sensitive characteristics, th...

Variable selection for interval-censored failure time data has recently attracted a great deal of attention along with the analysis of interval-censored data in both method developments and practical applications. Interval-censored data are a general type of time-to-event or failure time data where the failure time of interest is known or observed...

This article discusses regression analysis of clustered interval‐censored failure time data in the presence of a cured fraction or subgroup. Such data often occur in many areas, including epidemiological studies, medical studies, and social sciences. For the problem, a class of semiparametric transformation nonmixture cure models is presented and f...

Current status data arise when each subject is observed only once and the failure time of interest is only known to be either smaller or larger than the observation time rather than observed exactly. For the situation, due to the use of imperfect diagnostic tests, the failure status could often suffer misclassification or one observes misclassified...

Synthetic aperture radar automatic target recognition (SAR-ATR) is a hotspot in the field of remote sensing, which has been widely used in disaster monitoring, environmental monitoring, resource exploration, and crop yield estimates. In recent years, deep convolutional neural networks (DCNNs) have achieved promising performance among a variety of s...

This paper discusses regression analysis of interval-censored failure time data arising from the accelerated failure time model in the presence of informative censoring. For the problem, a sieve maximum likelihood estimation approach is proposed and in the method, the copula model is employed to describe the relationship between the failure time of...

Currently, the Internet of Things (IoT) provides individuals with real-time data processing and efficient data transmission services, relying on extensive edge infrastructures. However, those infrastructures may disclose sensitive information of consumers without authorization, which makes data access control to be widely researched. Ciphertext-pol...

In wireless sensor networks (WSNs), inefficient coverage does affect the quality of service (QoS), which the minimum exposure path (MEP) is traditionally used to handle. But intelligent mobile devices are generally of limited computation capability, local storage, and energy. Present methods cannot meet the demand of multiple target intrusion, lack...

Cox's proportional hazards model is the most commonly used model for regression analysis of failure time data and some methods have been developed for its variable selection under different situations. In this paper, we consider a general type of failure time data, case K interval-censored data, that include all of other types discussed as special...

The additive hazards model is one of the most commonly used models for regression analysis of failure time data and many inference procedures have been developed for it under various situations. In particular, Wang et al. (2018a, Computational Statistics and Data Analysis, 125, 1-9) discussed the situation where one observes informatively interval-...

This paper discusses the design of clinical trials where the primary endpoint is a recurrent event with the focus on the sample size calculation. For the problem, a few methods have been proposed but most of them assume a multiplicative treatment effect on the rate or mean number of recurrent events. In practice, sometimes the additive treatment ef...

Large amounts of data are widely stored in cyberspace. Not only can they bring much convenience to people’s lives and work, but they can also assist the work in the information security field, such as microexpression recognition and sentiment analysis in the criminal investigation. Thus, it is of great significance to recognize and analyze the sent...

enMotivated by the testing of genetic pleiotropy, we discuss a general class of hypothesis testing, the exclusive hypothesis test (EHT). A hypothesis test is an EHT if the null hypothesis can be divided into a set of exclusive sub-hypotheses, and a main difficulty for testing an EHT is the calculation of the p-value. To address this problem, we pro...

Case-1 and case-2 interval-censored failure time data commonly occur in medical research as well as other fields and many methods have been developed for their analysis under different frameworks. In this paper, we consider regression analysis of such data and present a general class of nonparametric transformation models. One major advantage of th...

A great deal of literature has been established for regression analysis of longitudinal data but most of the existing methods assume that covariates can be observed completely or at the same observation times for the response variable, and the observation process is independent of the response variable completely or given covariates. As pointed out...

The mobile phone is currently the most wid- ely used and most convenient photographic device. Like many optical imaging devices the camera of mobile ph- one are far from flawless, such as limited field of view and depth of focus in photos. Due to its limited computing power, it is not possible to use a mobile phone to fuse images. In addition, the...

Variable selection for failure time data with a cured fraction has been discussed by many authors but most of existing methods apply only to right-censored failure time data. In this paper, we consider variable selection when one faces interval-censored failure time data arising from a general class of generalized odds rate mixture cure models, and...

The existence of a cured subgroup happens quite often in survival studies and many authors considered this under various situations (Farewell in Biometrics 38:1041–1046, 1982; Kuk and Chen in Biometrika 79:531–541, 1992; Lam and Xue in Biometrika 92:573–586, 2005; Zhou et al. in J Comput Graph Stat 27:48–58, 2018). In this paper, we discuss the sit...

Clustered interval-censored failure time data occur in many areas and many methods have been proposed for their analysis. In practice, in addition to the clustering and interval censoring, such data may also present two other issues, cure fraction and informative cluster size, and it does not seem to exist an approach that can deal with all of thes...

Interval censoring and the existence of a cured subgroup occur quite often in survival studies and many procedures have been developed for dealing with each of the two issues individually or them together. In this paper, we discuss the situation where both issues exist and furthermore, interval censoring may be informative, for which there exists r...

In recent years, synthetic aperture radar (SAR) automatic target recognition has played a crucial role in multiple fields and has received widespread attention. Compared with optical image recognition with massive annotation data, lacking sufficient labeled images limits the performance of the SAR automatic target recognition (ATR) method based on...

Panel count data occur often in event history studies and in these situations, one observes only incomplete information, the number of events rather than the occurrence times of each event, about the point processes of interest.² Sometimes one may have to face a more complicated type of panel count data, mixed panel count data in which instead of t...

In this paper, we discuss regression analysis of censored failure time data when there exist missing covariates and more specifically, we will consider interval-censored data, a general form of censored data, and the nonignorable missing. Although many methods have been proposed in the literature for censored data with missing covariates, they only...

Rationale: Proxalutamide is a novel drug for the treatment of prostate cancer. However, to date, there are almost no reports on the pharmacokinetics of proxalutamide in vivo. Herein, a liquid chromatography tandem-mass spectrometry (LC/MS/MS) method was developed to determine the concentrations of proxalutamide in biological samples for pharmacoki...

Left truncation commonly occurs in many areas, and many methods have been proposed in the literature for the analysis of various types of left‐truncated failure time data. For the situation, a common approach is to conduct the analysis conditional on truncation times, and the method is relatively simple but may not be efficient. In this paper, we d...

This paper discusses variable selection in the context of joint analysis of longitudinal data and failure time data. A large literature has been developed for either variable selection or the joint analysis but there exists only limited literature for variable selection in the context of the joint analysis when failure time data are right censored....

In long-term follow-up studies on recurrent events, the observation patterns may not be consistent over time. During some observation periods, subjects may be monitored continuously so that each event occurence time is known. While during the other observation periods, subjects may be monitored discretely so that only the number of events in each p...

Variable selection is a commonly asked question in statistical analysis and has been extensively discussed under many contexts. In particular, many authors have investigated the problem under the survival analysis context. However, most of the existing methods for failure time data only deal with right-censored data and in this chapter, we will dis...

Missing data occur in almost every field and a great deal of literature has been established for the analysis of missing data with different types of missing mechanisms and under various models. Nonignorable missing data can be analyzed using nonparametric transformation models, which has not been discussed in the literature. In particular, assume...

In this article, we discuss the regression analysis of dependent current status data under the accelerated failure time model. There exist many literatures discussing the regression analysis of current status data under different models, but few literature discussing the regression problem of dependent current status data under the AFT model. Corre...

For the analysis of ultrahigh‐dimensional data, the first step is often to perform screening and feature selection to effectively reduce the dimensionality while retaining all the active or relevant variables with high probability. For this, many methods have been developed under various frameworks but most of them only apply to complete data. In t...

Variable selection has been discussed under many contexts and especially, a large literature has been established for the analysis of right‐censored failure time data. In this article, we discuss an interval‐censored failure time situation where there exist two sets of covariates with one being low‐dimensional and having possible nonlinear effects...

In this paper, we propose an efficient and energy-saving distributed network architecture based on clustering stratification to solve the information security problem of unmanned aerial vehicle ad hoc network communication. And a double-authentication watermarking strategy is designed. In order to ensure that the data collected by nodes can be sent...

This paper discusses variable or covariate selection for high-dimensional quadratic Cox model. Although many variable selection methods have been developed for standard Cox model or high-dimensional standard Cox model, most of them cannot be directly applied since they cannot take into account the important and existing hierarchical model structure...

Class imbalance is an important factor that affects the performance of deep learning models used for remote sensing scene classification. In this paper, we propose a random fine-tuning meta metric learning model (RF-MML) to address this problem. Derived from episodic training in meta metric learning, a novel strategy is proposed to train the model,...

The Editors-in-Chief have retracted this article [1] because it overlaps with articles by other authors that were simultaneously under consideration at different journals [2,3].

The case-cohort design is widely used as a means of reducing the cost in large cohort studies, especially when the disease rate is low and covariate measurements may be expensive, and has been discussed by many authors. In this paper, we discuss regression analysis of case-cohort studies that produce interval-censored failure time with dependent ce...

Doubly censored failure time data occur when the failure time of interest represents the elapsed time between two events, an initial event and a subsequent event, and the observations on both events may suffer censoring. A well-known example of such data is given by the acquired immune deficiency syndrome (AIDS) cohort study in which the two events...

The additive hazards model is one of the commonly used models for failure time data analysis and many authors have discussed its estimation under various situations. In this paper, we consider the same problem but under some inequality constraints when one faces current status data, for which it does not seem to exist an established estimation proc...

en The additive hazards model is one of the most commonly used regression models in the analysis of failure time data and many methods have been developed for its inference in various situations. However, no established estimation procedure exists when there are covariates with missing values and the observed responses are interval‐censored; both t...

This paper discusses regression analysis of the failure time data arising from case-cohort periodic follow-up studies, and one feature of such data, which makes their analysis much more difficult, is that they are usually interval-censored rather than right-censored. Although some methods have been developed for general failure time data, there doe...

Doubly truncated data often arise when event times are observed only if they fall within subject-specific intervals. We analyze doubly truncated data using nonparametric transformation models, where an unknown monotonically increasing transformation of the response variable is equal to an unknown monotonically increasing function of a linear combin...

The additive hazards model is one of the most popular regression models for analyzing failure time data, especially when one is interested in the excess risk or risk difference. Although a couple of methods have been developed in the literature for regression analysis of interval-censored data, a general type of failure time data, they may be compl...

Bivariate current status data occur in many areas and many authors have discussed their analysis and proposed many inference procedures [Jewell, N.P., van der Laan, M.J., and Lei, X. (2005), ‘Bivariate Current Status Data with Univariate Monitoring Times’, Biometrika, 92, 847–862; Wang, N., Wang, L., and McMahan, C.S. (2015), ‘Regression Analysis o...

The aim of gaze following is to estimate the gaze direction, which is useful for the understanding of human behaviour in various applications. However, it is still an open problem that has not been fully studied. In this paper, we present a novel framework for gaze following problem, where both the front/side face case and the back face case are ta...