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.
Novel Statistical Methods For The Analysis Of Meausred Genetic And Environmental Risk Factors In Twin Studies
Funder
National Health and Medical Research Council
Funding Amount
$478,314.00
Summary
Studies on twins are an important way to determine whether the risk of disease is likely to be influenced by genetic factors but have traditionally focussed on unmeasured factors. New epidemiological studies measure thousands of genetic variants on many participants. This project will extend methods for analysing data within and between twin pairs to determine whether risk factors are likely to be causal and therefore should be the subject of further designed studies based on intervention.
Statistical Methods For Handling Missing Data In Longitudinal Studies
Funder
National Health and Medical Research Council
Funding Amount
$198,000.00
Summary
Modern epidemiological research has a strong focus on studying the causes and consequences of major health outcomes over the life span. Studies are increasingly conducted on large cohorts of individuals over long periods of time, extending from before birth through to the later years of life. An example of this type of study is the Victorian Adolescent Health Cohort Study, which began in 1992 with participants aged 15 and is now seeking funding for a 9th wave of data collection in 2005. A major ....Modern epidemiological research has a strong focus on studying the causes and consequences of major health outcomes over the life span. Studies are increasingly conducted on large cohorts of individuals over long periods of time, extending from before birth through to the later years of life. An example of this type of study is the Victorian Adolescent Health Cohort Study, which began in 1992 with participants aged 15 and is now seeking funding for a 9th wave of data collection in 2005. A major challenge that arises in analysing data from studies of this kind is the difficulty created by the occurrence of missing data. In longitudinal studies with multiple measurement occasions, participants rarely complete all waves of data collection, and even when present an individual may not provide data on all study variables. Common practice in analysing such data is to omit individuals entirely if they have a missing value on any of the variables required for the analysis in question. This approach can lead to major biases in conclusions, by excluding individuals in whom patterns of association may be quite different than among those retained, and at best leads to loss of reliability in findings due to the reduction in numbers available for analysis. Recent statistical research has led to a range of new techniques for better handling of missing data in such studies, including the method of multiple imputation (MI), under which multiple copies of the dataset are created with imputed values filled in for the missing values. This approach has enormous potential for helping to produce better answers from large longitudinal studies but a number of issues require research to ensure that the method is made available to researchers in a convenient form and, most importantly, used in a way that leads to sound conclusions. This project will address many of these issues, leading to enhanced capacity to extract valuable information from large epidemiological studies.Read moreRead less
Prof Speed is a statistician specializing in bioinformatics and computational biology, applying my skills in support of basic research in molecular and cell biology and genetics.
I am a statistician specializing in bioinformatics and computational biology, applying my skills in support of basic research in molecular and cell biology and genetics.
NONPARAMETRIC STATISTICS. Nonparametric statistical methods are techniques that implicitly choose statistical models from exceptionally large and highly adaptive classes. The project aims to develop innovative and practicable nonparametric methods in four areas: Statistical Smoothing, Data Mining, Mixture Methods and Robust Inference. The significance of the work lies in its novelty, the breadth of its practical motivation, and its position at the leading edge of contemporary work in statisti ....NONPARAMETRIC STATISTICS. Nonparametric statistical methods are techniques that implicitly choose statistical models from exceptionally large and highly adaptive classes. The project aims to develop innovative and practicable nonparametric methods in four areas: Statistical Smoothing, Data Mining, Mixture Methods and Robust Inference. The significance of the work lies in its novelty, the breadth of its practical motivation, and its position at the leading edge of contemporary work in statistics. Expected outcomes include new technologies for data analysis.Read moreRead less
Statistical Methods For The Analysis Of Trends In Coronary Heart Disease
Funder
National Health and Medical Research Council
Funding Amount
$112,747.00
Summary
Coronary heart disease is a leading cause of mortality, morbidity and medical costs in Australia. During the 1950's and 1960's, rates of coronary disease increased rapidly, then in the late 1960's they started to decline. This decrease has continued steadily for 30 years. While some other westernised countries have had this same experience, in Eastern Europe and in many developing countries coronary disease is increasing. There is a huge amount of evidence from experimental studies in animal and ....Coronary heart disease is a leading cause of mortality, morbidity and medical costs in Australia. During the 1950's and 1960's, rates of coronary disease increased rapidly, then in the late 1960's they started to decline. This decrease has continued steadily for 30 years. While some other westernised countries have had this same experience, in Eastern Europe and in many developing countries coronary disease is increasing. There is a huge amount of evidence from experimental studies in animal and human subjects and population studies in many countries that the major determinants of coronary disease are high blood pressure, cigarette smoking and high cholesterol (and other lipids) as well as dietary factors, obesity and physical inactivity. Recently several large multicentre studies have found unexpectedly weaker associations between heart risk factors and disease rates. It is hypothesised that this is due to inappropriate analyses in which data from populations at different stages of the coronary epidemic have been combined. The aim of this study is to develop improved statistical methodology to help understand recent findings from large scale studies, such as the World Health Organization's MONICA Project, the US ARIC study and the Seven Countries study. It will provide new theoretical results and statistical software for their implementation. From a public health perspective the most important outcome will be clarification of recent apparently anomalous findings about the importance of established risk factors and effective treatments in reducing coronary disease at the population level.Read moreRead less
Dynamic prediction models in Australian rules football using real time performance statistics. The study is a collaborative venture with Champion Data, the Australian leader in the collection and transmission of real time sporting data, and official provider of the Australian Football League (AFL) statistics. The aim is to develop a real time on line predictive model for AFL football. The model will use the statistics Champion Data collect as the match progresses as inputs to continually updat ....Dynamic prediction models in Australian rules football using real time performance statistics. The study is a collaborative venture with Champion Data, the Australian leader in the collection and transmission of real time sporting data, and official provider of the Australian Football League (AFL) statistics. The aim is to develop a real time on line predictive model for AFL football. The model will use the statistics Champion Data collect as the match progresses as inputs to continually update estimates of the probabilities of various outcomes of interest such as the winner of the match and the margin of victory. The project will assist Champion in their strategic aim to provide an on line form guide.Read moreRead less
Bayesian Statistical Inference for Implicitly defined Probability Models. Bayesian statistics has recently been used to provide solutions for a large number of hitherto intractable problems in science and technology. The success of Bayesian statistics has mainly been due to the application of so-called Markov chain Monte Carlo computational techniques. We aim to improve these algorithms, by providing fast, simple and efficient computational implementations. We will use the results to give ins ....Bayesian Statistical Inference for Implicitly defined Probability Models. Bayesian statistics has recently been used to provide solutions for a large number of hitherto intractable problems in science and technology. The success of Bayesian statistics has mainly been due to the application of so-called Markov chain Monte Carlo computational techniques. We aim to improve these algorithms, by providing fast, simple and efficient computational implementations. We will use the results to give insight by carefully quantifying and modelling uncertainty for such topics as the transmission rate of infectious diseases, the spatial distribution of plant and animal species, investigating biological theory for the genome of a virus, and changes in human fertility.Read moreRead less
A Program Of Methodological And Collaborative Research In Biostatistics And Population Health
Funder
National Health and Medical Research Council
Funding Amount
$264,081.00
Summary
Biostatistics is a critical component of health and medical research, especially for studies in population health. However, there is an increasing gap between supply and demand for high-level biostatistical input. This proposal combines novel methodological research into methods for analysing incomplete data, with collaborative research applying new ideas and complex analyses to important health problems. The fellowship will facilitate my development as a future leader in this key area.