Sy Han Chiou

Sy Han Chiou
University of Texas at Dallas | UTD · School of Natural Sciences and Mathematics

Doctor of Philosophy

About

33
Publications
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254
Citations

Publications

Publications (33)
Article
In biomedical studies, survival data with a cure fraction (the proportion of subjects cured of disease) are commonly encountered. The mixture cure and bounded cumulative hazard models are two main types of cure fraction models when analyzing survival data with long-term survivors. In this article, in the framework of the Cox proportional hazards mi...
Article
Truncated survival data arise when the event time is observed only if it falls within a subject specific region. The conventional risk‐set adjusted Kaplan–Meier estimator or Cox model can be used for estimation of the event time distribution or regression coefficient. However, the validity of these approaches relies on the assumption of quasi‐indep...
Article
There is often delayed entry into observational studies, which results in left truncation. In the estimation of the distribution of time-to-event from left-truncated data, standard survival analysis methods require quasi-independence between the truncation time and event time. Incorrectly assuming quasi-independence may lead to biased estimation. W...
Preprint
Full-text available
Recurrent event analyses have found a wide range of applications in biomedicine, public health, and engineering, among others, where study subjects may experience a sequence of event of interest during follow-up. The R package reReg (Chiou and Huang 2021) offers a comprehensive collection of practical and easy-to-use tools for regression analysis o...
Article
Single-index models have gained increased popularity in time-to-event analysis owing to their model flexibility and advantage in dimension reduction. In this paper, we propose a semiparametric framework for the rate function of a recurrent event counting process by modelling its size and shape components with single-index models. With additional mo...
Preprint
With the availability of massive amounts of data from electronic health records and registry databases, incorporating time-varying patient information to improve risk prediction has attracted great attention. To exploit the growing amount of predictor information over time, we develop a unified framework for landmark prediction using survival tree...
Article
Two major challenges arise in regression analyses of recurrent event data: first, popular existing models, such as the Cox proportional rates model, may not fully capture the covariate effects on the underlying recurrent event process; second, the censoring time remains informative about the risk of experiencing recurrent events after accounting fo...
Article
Tree‐based methods are popular nonparametric tools in studying time‐to‐event outcomes. In this article, we introduce a novel framework for survival trees and ensembles, where the trees partition the dynamic survivor population and can handle time‐dependent covariates. Using the idea of randomized tests, we develop generalized time‐dependent Receive...
Article
Purpose: In several biomedical studies, one or more exposures of interest may be subject to nonrandom missingness because of the failure of the measurement assay at levels below its limit of detection. This issue is commonly encountered in studies of the metabolome using tandem mass spectrometry-based technologies. Owing to a large number of metab...
Article
Truncation is a mechanism that permits observation of selected subjects from a source population; subjects are excluded if their event times are not contained within subject-specific intervals. Standard survival analysis methods for estimation of the distribution of the event time require quasi-independence of failure and truncation. When quasi-ind...
Preprint
Tree-based methods are popular nonparametric tools in studying time-to-event outcomes. In this article, we introduce a novel framework for survival trees and forests, where the trees partition the dynamic survivor population and can handle time-dependent covariates. Using the idea of randomized tests, we develop generalized time-dependent ROC curve...
Article
Background: The 2016 World Health Organization Classification of Central Nervous System Tumors categorizes gliomatosis cerebri growth pattern (GC) as a subgroup of diffuse infiltrating gliomas, defined by extent of brain involvement on magnetic resonance imaging (MRI). Clinical and radiographic features in GC patients are highly heterogeneous; how...
Article
Rural-urban disparities in the prevalence of mental disorders and in access to mental health care among veterans have been documented, but no consistent pattern has emerged. Mixed research findings may be because of broad distinctions between rural and urban that mask intrarural variation in veteran mental health. This study explored the extent to...
Article
Truncated survival data arise when the event time is observed only if it falls within a subject-specific region, known as the truncation set. Left-truncated data arise when there is delayed entry into a study, such that subjects are included only if their event time exceeds some other time. Quasi-independence of truncation and failure refers to fac...
Article
In several common study designs, regression modeling is complicated by the presence of censored covariates. Examples of such covariates include maternal age of onset of dementia that may be right censored in an Alzheimer's amyloid imaging study of healthy subjects, metabolite measurements that are subject to limit of detection censoring in a case‐c...
Article
Full-text available
Panel count data arise in many applications when the event history of a recurrent event process is only examined at a sequence of discrete time points. In spite of the recent methodological developments, the availability of their software implementations has been rather limited. Focusing on a practical setting where the effects of some time‐indepen...
Article
Full-text available
Background: We conducted an observational study evaluating the association between uric acid, mean platelet volume (MPV), and high-density lipoprotein (HDL) with complications and outcomes of patients with sepsis in a critical care setting. Methods: We followed patients with a diagnosis of severe sepsis and septic shock for a maximum of 28 days....
Article
Full-text available
Panel count data arise when the number of recurrent events experienced by each subject is observed intermittently at discrete examination times. The examination time process can be informative about the underlying recurrent event process even after conditioning on covariates. We consider a semiparametric accelerated mean model for the recurrent eve...
Article
Full-text available
Aims: Left ventricular (LV) diastolic dysfunction may lead to heart failure. A high body mass index (BMI) is associated with worse LV diastolic function. However, knowledge of the longitudinal relation between changes in BMI and LV diastolic function is limited. Methods and results: We retrospectively identified 165 asymptomatic individuals (age...
Article
Background: Limited data on stroke exist for Costa Rica. Therefore, we created a stroke registry out of patients with stroke seen in the Acute Stroke Unit of the Hospital Calderon Guardia. Methods: We analyzed 1319 patients enrolled over a 7-year period, which incorporated demographic, clinical, laboratory, and neuroimaging data. Results: The...
Article
Full-text available
A recent paper in Neurology used statistical techniques to investigate the integrity of the randomization in 33 clinical trials conducted by a group of investigators. Without justification, the approach assumed that there would be no impact of correlation among baseline variables. We investigated the impact of correlation on the conclusions of the...
Data
R code for simulations. (PDF)
Article
Full-text available
Length-biased sampling appears in many observational studies, including epidemiological studies, labor economics and cancer screening trials. To accommodate sampling bias, which can lead to substantial estimation bias if ignored, we propose a class of doubly-weighted rank-based estimating equations under the accelerated failure time model. The gene...
Article
Full-text available
Background: Persistent Pseudomonas aeruginosa (PPA) infection promotes lung function deterioration in children with cystic fibrosis (CF). Although early CF diagnosis through newborn screening (NBS) has been shown to provide nutritional/growth benefit, it is unclear whether NBS lowers the risk of PPA infection and how the effect of NBS vary with ag...
Article
Full-text available
Recurrent event data arise frequently in various fields such as biomedical sciences, public health, engineering, and social sciences. In many instances, the observation of the recurrent event process can be stopped by the occurrence of a correlated failure event, such as treatment failure and death. In this article, we propose a joint scale-change...
Chapter
Outbreaks of influenza pose a serious threat to communities and hospital resources. It is important for health care providers not only to know the seasonal trend of influenza, but also to be alarmed when unusual outbreaks occur as soon as possible for more efficient, proactive resource allocation. Google Flu Trends data showed a good match in trend...
Article
The induced smoothing technique overcomes the difficulties caused by the non-smoothness in rank-based estimating functions for accelerated failure time models, but it is only natural when the estimating function has Gehan's weight. For a general weight, the induced smoothing method does not provide smooth estimating functions that can be easily eva...
Article
Clustered failure times often arise from studies with stratified sampling designs where it is desired to reduce both cost and sampling error. Semiparametric accelerated failure time (AFT) models have not been used as frequently as Cox relative risk models in such settings due to lack of efficient and reliable computing routines for inferences. The...
Article
Full-text available
Accelerated failure time (AFT) models are alternatives to relative risk models which are used extensively to examine the covariate effects on event times in censored data regression. Nevertheless, AFT models have been much less utilized in practice due to lack of reliable computing methods and software. This paper describes an R package aft g gee t...
Article
The semiparametric accelerated failure time (AFT) model is not as widely used as the Cox relative risk model due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations for censored data provide promising tools to make the AFT models more attractive in practice. For multivariate AFT...
Article
In survival analysis, semiparametric accelerated failure time (AFT) models directly relate the predicted failure times to covariates and are a useful alternative to relative risk models. Recent developments in rank-based estimation and least squares estimation provide promising tools to make the AFT models more attractive in practice. In this disse...

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