A Quantile Regression Model for Failure-Time Data with Time-Dependent Covariates

Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This paper provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset

General Semiparametric Shared Frailty Model Estimation and Simulation with frailtySurv

The R package frailtySurv for simulating and fitting semi-parametric shared frailty models is introduced. Package frailtySurv implements semi-parametric consistent estimators for a variety of frailty distributions, including gamma, log-normal, inverse Gaussian and power variance function, and provides consistent estimators of the standard errors of the parameters' estimators. The parameters' estimators are asymptotically normally distributed, and therefore statistical inference based on the results of this package, such as hypothesis testing and confidence intervals, can be performed using the normal distribution. Extensive simulations demonstrate the flexibility and correct implementation of the estimator. Two case studies performed with publicly available datasets demonstrate applicability of the package. In the Diabetic Retinopathy Study, the onset of blindness is clustered by patient, and in a large hard drive failure dataset, failure times are thought to be clustered by the hard drive manufacturer and model

Older Woman Workers: Met and Unmet Needs for Health and Wellbeing in the Workplace

Older women workers report experiencing occupational injustices however the literature focuses on barriers faced rather than understanding the needs-based strategies empowering women as they age at work. This study engaged women aged 55 and older in a participatory action research project defining and examining strategies for older women workers’ health and wellbeing. In Phase 1, a key informant advisory group (N = 4) defined the problem and guided the design of an open answer survey conducted with 72 older women in work. Three categories emerged informing the fundamental, instrumental, and contextual needs of older women workers. Meeting fundamental needs may proactively retain older women in work, while addressing instrumental needs may inform women’s prioritizing their needs as they age at work. This suggests a contextual health promotion approach will best serve older women’s needs to flourish in work

Assessment of the sustainability of Victorian abalone resources

University of Technology, Sydney. Faculty of Science.Many of the world's abalone fisheries have collapsed and in the past 25 years global abalone production has almost halved. Australia now produces 55% of the world's wild abalone and its abalone fisheries are close to, or above, their limits for sustainable yield. Although recruitment over-fishing has generally been singled out as the principal cause of collapse, other factors related to changes in environmental patterns and ecosystem dynamics are also implicated. It is in this context that the central question of this thesis about the sustainability of Victorian abalone populations is posed. The answer to this question would be obvious with the hindsight that follows a collapse, but for a predominantly healthy fishery this is a different proposition. This thesis presents one of the few comprehensive frameworks for abalone resources assessment and sustainable management worldwide. The key elements in the overall governance of the fishery are explored through a compilation of formally published papers and publicly available assessment documents. Topics for these works range from fishery independent abundance surveys, through fishery assessment modelling, biological performance indicators and management strategies to reporting outcomes for ecological sustainability objectives under state and federal legislation. This is done in a mostly quantitative framework that incorporates explicit linkages between assessment and management decision-making processes. Our assessments indicate that the Victorian blacklip resource has been largely sustainable during the past 40 years. The management history of the fishery suggests that this owes much to prudent introduction of a broad range of input and output controls at the behest of industry. However, recent instances of localised depletion, a large but unquantified illegal catch and model predictions of declining mature biomass suggest that there is no room for complacency. In contrast to blacklip, greenlip abalone resources are in need of restorative action and the future existence of a commercial greenlip fishery in Victoria is problematic. It is vitally important that we continue to refine our management, attempt to understand its limitations, address the difficult ecological issues and avail ourselves of emerging technologies that enable greater efficiency and precision in the scale of assessment and management. Finally, having an effective assessment and management framework is insufficient on its own to demonstrate the sustainability of Victorian abalone resources. To properly satisfy legislation for resource sustainability there is a need to document and report the outcomes against specific assessment criteria audited by an independent body on a regular basis. Continued approval to export Victorian abalone overseas is contingent on meeting this requirement

Consistent distribution-free KK-sample and independence tests for univariate random variables

A popular approach for testing if two univariate random variables are statistically independent consists of partitioning the sample space into bins, and evaluating a test statistic on the binned data. The partition size matters, and the optimal partition size is data dependent. While for detecting simple relationships coarse partitions may be best, for detecting complex relationships a great gain in power can be achieved by considering finer partitions. We suggest novel consistent distribution-free tests that are based on summation or maximization aggregation of scores over all partitions of a fixed size. We show that our test statistics based on summation can serve as good estimators of the mutual information. Moreover, we suggest regularized tests that aggregate over all partition sizes, and prove those are consistent too. We provide polynomial-time algorithms, which are critical for computing the suggested test statistics efficiently. We show that the power of the regularized tests is excellent compared to existing tests, and almost as powerful as the tests based on the optimal (yet unknown in practice) partition size, in simulations as well as on a real data example.Comment: arXiv admin note: substantial text overlap with arXiv:1308.155

Discrete-time Competing-Risks Regression with or without Penalization

Many studies employ the analysis of time-to-event data that incorporates competing risks and right censoring. Most methods and software packages are geared towards analyzing data that comes from a continuous failure time distribution. However, failure-time data may sometimes be discrete either because time is inherently discrete or due to imprecise measurement. This paper introduces a novel estimation procedure for discrete-time survival analysis with competing events. The proposed approach offers two key advantages over existing procedures: first, it expedites the estimation process for a large number of unique failure time points; second, it allows for straightforward integration and application of widely used regularized regression and screening methods. We illustrate the benefits of our proposed approach by conducting a comprehensive simulation study. Additionally, we showcase the utility of our procedure by estimating a survival model for the length of stay of patients hospitalized in the intensive care unit, considering three competing events: discharge to home, transfer to another medical facility, and in-hospital death