Diagnostics For Mixture Regression Models: Applications To Public Health
Funder
National Health and Medical Research Council
Funding Amount
$128,250.00
Summary
In many public health studies, finite mixture regression models are often used to analyse data arising from heterogeneous populations. It is important to assess the stability of parameter estimates and the validity of statistical inferences when the underlying assumptions appear to be violated, but appropriate diagnostics are lacking in the literature. This research aims to develop effective diagnostic methods for assessing the adequacy of mixture regression models and the sensitivity of accompa ....In many public health studies, finite mixture regression models are often used to analyse data arising from heterogeneous populations. It is important to assess the stability of parameter estimates and the validity of statistical inferences when the underlying assumptions appear to be violated, but appropriate diagnostics are lacking in the literature. This research aims to develop effective diagnostic methods for assessing the adequacy of mixture regression models and the sensitivity of accompanying test statistics. The methodology developed will enable health care professionals to focus on substantive issues and to draw accurate and valid conclusions inferred from correlated and over-dispersed outcomes. In the presence of anomalous observations, the influence diagnostics can provide insights into the source of heterogeneity and the apparent over-dispersion, while accommodating the inherent correlation due to the longitudinal study design or nested data structure. Significance of the research lies in its scientific novelty and the breadth of its practical applications. The benefits to public health will accrue both nationally and internationally. For the empirical studies that motivated and are linked to this research, evaluation of health outcomes has significant implications in the prevention and control of recurrent urinary tract infections, hospital strategic planning, and post-stroke care and rehabilitation management. Moreover, appropriate assessment of a physical activity intervention for older adults is pertinent to falls prevention and reduction of musculoskeletal disorders among sedentary seniors.Read moreRead less
Hierarchical Finite Mixture Modelling Of Health Outcomes: A Risk-adjusted Random Effects Approach
Funder
National Health and Medical Research Council
Funding Amount
$117,000.00
Summary
In medical and health studies, finite mixture regression models have been used to analyze data arising from heterogeneous populations. Traditionally, the application of mixture models is mainly concerned with finite normal mixtures. Recent computational advances and methodological developments have enhanced the extension of the method to non-normal finite mixtures, such as the modelling of discrete responses in finite mixture of generalized linear models and overlapping phases of failure time da ....In medical and health studies, finite mixture regression models have been used to analyze data arising from heterogeneous populations. Traditionally, the application of mixture models is mainly concerned with finite normal mixtures. Recent computational advances and methodological developments have enhanced the extension of the method to non-normal finite mixtures, such as the modelling of discrete responses in finite mixture of generalized linear models and overlapping phases of failure time data in the context of survival analysis. However, due to the hierarchical study design or the data collection procedure, the inherent correlation structure and-or clustering effects present may contribute to extra variations and violation of the independence assumption, resulting in spurious associations and misleading inferences based on the finite mixture model. This project aims to present a unified approach to accommodate both heterogeneity and dependency of observations, by incorporating random effects into finite mixture regression models. The new methodology will provide an integrated framework to analyze heterogeneous and correlated health outcomes. Three empirical studies are considered, namely, evaluation of an occupational injury reduction intervention, length of hospital stay modeling, and analysis of survival times of patients after cardiac surgery. The long term benefits to bioscience are accurate and valid conclusions inferred from medical and health studies, as well as the correct identification of high-risk subgroups. For the three application areas of this project, the improved analyses will specifically enable the evaluation of a participatory ergonomics intervention, the assessment of hospital efficiency and factors influencing length of hospitalization, and the determination of effectiveness of treatments prescribed pre- and post- operation, respectively.Read moreRead less
Meta-research: Using Research To Increase The Value Of Health And Medical Research
Funder
National Health and Medical Research Council
Funding Amount
$631,370.00
Summary
Improving the return on investment in health and medical research will produce more and faster discoveries that enhance the lives of all Australians. Many problems in the research process are well known and have been pervasive for decades. I will use the research process to improve the research process. I will improve Australia's health and medical research workforce and the quality of the research they produce, creating benefits in multiple fields that last long into the future.
Development Of Statistical Methodologies And Application To Clinical Cancer Studies
Funder
National Health and Medical Research Council
Funding Amount
$428,065.00
Summary
Integrating different layers of information coming from the recent ‘-omics’ technologies can help improving the treatment and the prevention of complex diseases. In particular, the identification of molecular markers of different types can be used for better diagnostics and prognosis in cancer and immune diseases. This project will develop innovative statistical solutions to handle and make sense of the vast amount of biological data that are routinely generated in the laboratories.
Bayesian statistical models for understanding outcomes and improving decision-making for women screened for breast cancer. This project has two key benefits: (i) the development of frontier statistical methods for spatio-temporal analysis and data synthesis, which are imperative in a wide range of disciplines; and (ii) the application of these methods for improved understanding of breast cancer outcomes for women screened in Queensland. The project results will lead to direct health and financi ....Bayesian statistical models for understanding outcomes and improving decision-making for women screened for breast cancer. This project has two key benefits: (i) the development of frontier statistical methods for spatio-temporal analysis and data synthesis, which are imperative in a wide range of disciplines; and (ii) the application of these methods for improved understanding of breast cancer outcomes for women screened in Queensland. The project results will lead to direct health and financial benefits through targeted policies for increasing screening uptake and reducing cancer morbidity and mortality and therefore health spending in this area. Importantly, the project represents an excellent training opportunity to develop a PhD candidate into an experienced interdisciplinary researcher.Read moreRead less
Goodness-of-fit Testing Of Log-link Models For Categorical Outcome Data
Funder
National Health and Medical Research Council
Funding Amount
$260,863.00
Summary
Information about the health consequences of exposure to causal factors is obtained from mathematical models of observed data. Incorrect inferences are possible if the model does not adequately represent the data. Relative risk models are recommended for observations over time on a cohort of subjects, but it is not known how best to assess the adequacy of such models. This project will assess the performance of summary measures of goodness-of-fit when applied to relative risk models.
New methods for analysing marketing Databases in the age of digital media. This is a time of enormous and rapid change in many areas of Australian business due to the introduction and widespread dissemination of digital media. It has resulted in the accumulation of large integrated databases of customer information and their transactions. Firms in all countries, particularly those challenged by distance and size, like Australia, are now seeking to find ways to make better use of their voluminous ....New methods for analysing marketing Databases in the age of digital media. This is a time of enormous and rapid change in many areas of Australian business due to the introduction and widespread dissemination of digital media. It has resulted in the accumulation of large integrated databases of customer information and their transactions. Firms in all countries, particularly those challenged by distance and size, like Australia, are now seeking to find ways to make better use of their voluminous information so as to make efficiency gains in their business processes, strategic decision-making and customer relationship management. Our project aims to contribute to the ARC priority research goal of smart information use by developing new methodologies for the analysis of these large integrated databases.Read moreRead less
Design And Analysis Of Interrupted Time Series Studies In Health Care Research: Resolution Of Methodological Issues
Funder
National Health and Medical Research Council
Funding Amount
$307,125.00
Summary
An interrupted time series (ITS) study involves a population observed on multiple occasions before and after the implementation of an intervention program. However, methods for statistical analysis and designing such studies have not been well developed and many statistical analyses of such studies are flawed. This proposal will investigate appropriate methods for design and analysis, and develop guidelines and software for its implementation by health researchers.
WaterLog - A mathematical model to implement recommendations of The Wentworth Group. In 2003, The Wentworth Group of Concerned Scientists released their 'Blueprint for a national water plan' with the primary objective to 'protect river health and the rights of all Australians to clean usable water'. Currently, there are significant water restrictions in all the Australian mainland capital cities. In January 2007, the Prime Minister of Australia, announced a bold plan to rescue the Murray-Darling ....WaterLog - A mathematical model to implement recommendations of The Wentworth Group. In 2003, The Wentworth Group of Concerned Scientists released their 'Blueprint for a national water plan' with the primary objective to 'protect river health and the rights of all Australians to clean usable water'. Currently, there are significant water restrictions in all the Australian mainland capital cities. In January 2007, the Prime Minister of Australia, announced a bold plan to rescue the Murray-Darling Basin. The plan incorporates political management changes, and an investment of $10Bn. Now is the time to develop improved techniques for management of water storage systems. This project will develop the fundamental mathematical principles required for this improved management.Read moreRead less
Assessing and enhancing the quality of longitudinal survey data. Australia has begun investing heavily in the collection of population-wide longitudinal survey data. Most of that effort has focused first on collection and dissemination and second on analysis, with scant attention paid to the quality of data collected. This is unfortunate given that longitudinal surveys exhibit many problems (e.g., attrition, panel conditioning, and seam effects) that are not relevant in more ubiquitous cross-sec ....Assessing and enhancing the quality of longitudinal survey data. Australia has begun investing heavily in the collection of population-wide longitudinal survey data. Most of that effort has focused first on collection and dissemination and second on analysis, with scant attention paid to the quality of data collected. This is unfortunate given that longitudinal surveys exhibit many problems (e.g., attrition, panel conditioning, and seam effects) that are not relevant in more ubiquitous cross-section of surveys. Without adequate resources devoted to these methodological issues, the quality of substantive research will be questioned and interest from potential users decline. Maximizing the investment being made in longitudinal data thus requires a complementary investment in methodological research.Read moreRead less