Failure time data analysis, or survival analysis, is involved in various research fields, such as medicine and public health. One basic assumption in standard survival analysis is that every individual in the study population will eventually experience the event of interest. However, this assumption is usually violated in practice, for example when the variable of interest is the time to relapse of a curable disease resulting in the existence of long-term survivors. Also, presence of unobservable risk factors in the group of susceptible individuals may introduce heterogeneity to the population, which is not properly addressed in standard survival models. Moreover, the individuals in the population may be grouped in clusters, where there are associations among observations from a cluster. There are methodologies in the literature to address each of these problems, but there is yet no natural and satisfactory way to accommodate the coexistence of a non-susceptible group and the heterogeneity in the susceptible group under a univariate setting. Also, various kinds of associations among survival data with a cure are not properly accommodated. To address the above-mentioned problems, a class of models is introduced to model univariate and multivariate data with long-term survivors. A semiparametric cure model for univariate failure time data with long-term survivors is introduced. It accommodates a proportion of non-susceptible individuals and the heterogeneity in the susceptible group using a compound- Poisson distributed random effect term, which is commonly called a frailty. It is a frailty-Cox model which does not place any parametric assumption on the baseline hazard function. An estimation method using multiple imputation is proposed for right-censored data, and the method is naturally extended to accommodate interval-censored data. The univariate cure model is extended to a multivariate setting by introducing correlations among the compound- Poisson frailties for individuals from the same cluster. This multivariate cure model is similar to a shared frailty model where the degree of association among each pair of observations in a cluster is the same. The model is further extended to accommodate repeated measurements from a single individual leading to serially correlated observations. Similar estimation methods using multiple imputation are developed for the multivariate models. The univariate model is applied to a breast cancer data and the multivariate models are applied to the hypobaric decompression sickness data from National Aeronautics and Space Administration, although the methodologies are applicable to a wide range of data sets. / published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

published_or_final_version / abstract / toc / Statistics and Actuarial Science / Master / Master of Philosophy

Survival analysis is a well developed area which explores time to single event analysis. In some cases, however, such methods may not adequately capture the disease process as the disease progression may involve intermediate events of interest. Multistate models incorporate multiple events or states. This thesis proposes to demystify the theory of multistate models through an application based approach. We present the key components of multistate models, relevant derivations, model diagnostics and techniques for modeling the effect of covariates on transition intensities. The methods that are developed in the thesis are applied to HIV and TB data partly sourced from CAPRISA and the HPP programmes in the University of KwaZulu-Natal. HIV progression is investigated through the application of a five state Markov model with reversible transitions such that state 1: CD4 count 500, state 2: 350 CD4 count < 500, state 3: 200 CD4 count < 350, state 4: CD4 count < 200 and state 5: ARV initiation. The mean sojourn time in each state and transition probabilities are presented as well as the effect of covariates namely age, gender and baseline CD4 count on transition rates. A key finding, consistent with previous research, is that the rate of decline in CD4 count tends to decrease at lower levels of the marker. Further, patients enrolling with a CD4 count less than 350 had a far lower chance of immune recovery and a substantially higher chance of immune deterioration compared to patients with a higher CD4 count. We noted that older patients tend to progress more rapidly through the disease than younger patients. / Thesis (M.Sc.)-University of KwaZulu-Natal, Westville, 2011.

Multi-modal biometrics is one of the most promising avenues to address the performance problems in biometrics-based personal authentication systems. While uni-modal biometric systems have bolstered personal authentication better than traditional security methods, the main challenges remain the restricted degrees of freedom, non-universality and spoof attacks of the traits. In this research work, we investigate the performance improvement in bi-modal biometrics authentication systems based on the physiological trait, the iris, and behavioral trait, the signature. We investigate a model to detect the largest non-occluded rectangular part of the iris as a region of interest (ROI) from which iris features are extracted by a cumulative-sums-based grey change analysis algorithm and Gabor Filters. In order to address the space complexity of biometric systems, we proposed two majority vote-based algorithms which compute prototype iris features codes as the reliable specimen templates. Experiments obtained a success rate of 99.6%. A text-based directional signature verification algorithm is investigated. The algorithm verifies signatures, even when they are composed of symbols and special unconstrained cursive characters which are superimposed and embellished. The experimental results show that the proposed approach has an improved true positive rate of 94.95%. A user-specific weighting technique, the user-score-based, which is based on the different degrees of importance for the iris and signature traits of an individual, is proposed. Then, an intelligent dual ν-support vector machine (2ν-SVM) based fusion algorithm is used to integrate the weighted match scores of the iris and signature modalities at the matching score level. The bi-modal biometrics system obtained a false rejection rate (FRR) of 0.008, and a false acceptance rate (FAR) of 0.001. / Thesis (Ph.D)-University of KwaZulu-Natal, Westville, 2010.

When subjects are recruited through a cross-sectional survey they have already experienced the initiation of the event of interest, say the onset of a disease. This method of recruitment results in the fact that subjects with longer duration of the disease have a higher chance of being selected. It follows that censoring in such a case is not non-informative. The application of standard techniques for right-censored data thus introduces a bias to the analysis; this is referred to as length-bias. This paper examines the case where the subjects are assumed to enter the study at a uniform rate, allowing for the analysis in a more efficient unconditional manner. In particular, a new method for unconditional analysis is developed based on the framework of a conditional estimator. This new method is then applied to the several data sets and compared with the conditional technique of Tsai [23].

Thesis (M.S.)--Georgia State University, 2007. / Title from file title page. Yichuan Zhao, committee chair; Yu-Sheng Hsu , Xu Zhang, Yuanhui Xiao , committee members. Electronic text (54 p.) : digital, PDF file. Description based on contents viewed Feb. 25, 2008. Includes bibliographical references (p. 30-32).

Thesis (Ph. D.)--University of Canterbury, 2008. / Typescript (photocopy). "October 2008." Includes bibliographical references (p. 230-243). Also available via the World Wide Web.

Thesis (Ph.D. in Analytic Health Sciences) -- University of Colorado Denver, 2007. / Typescript. Includes bibliographical references (leaves 46-48). Free to UCD affiliates. Online version available via ProQuest Digital Dissertations;

Thesis (M. Phil.)--University of Hong Kong, 2009. / Includes bibliographical references (leaves 94-97) Also available in print.

Thesis (Ph. D.)--University of Washington, 1997. / Vita. Includes bibliographical references (p. [132]-146).