Goodness-of-fit Testing And Extensions Of Relative Risk Models
Funder
National Health and Medical Research Council
Funding Amount
$380,558.00
Summary
Information about the health consequences of exposure to causal factors is obtained from mathematical models of observed 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 or whether they can be applied to ordered outcomes or multiple measurements on the same individuals. These research aims to address those issues, and thereby to increase the practical usefulness of these models.
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
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.
Strategies For Handling Missing Data In The Development, Validation And Implementation Of Clinical Risk Prediction Tools
Funder
National Health and Medical Research Council
Funding Amount
$451,692.00
Summary
Tools that predict the future outcome of disease are common. Missing data is a problem in studies that develop and validate such tools and affects their validity because simple approaches to dealing with missing data are biased. We will develop statistical methodology in this area and compare the performance of this and other methodologies. Alongside this methodological work we will re-assess existing prediction tools and develop new tools in the areas of cardiac surgery and kidney disease.
Modelling claim dependencies for the general insurance industry with economic capital in view: an innovative approach with stochastic processes. This project will develop and enhance multi-dimensional models used to describe and assess the risks borne by general insurers. These innovative methods, which will be directly applicable by the industry, will strengthen the efficiency and the safety of the Australian economy.
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.
Models for Australian Electricity Derivatives. Electricity derivatives, such as electricity futures and options are used to manage the risk associated with volatility in prices of electricity. This project aims to develop models for pricing electricity derivatives specifically suited for Australia. Because of the non-storable nature of electricity the standard option pricing principle of "no-arbitrage" does not apply to electricity options, such as caps and floors, but applies to options on elec ....Models for Australian Electricity Derivatives. Electricity derivatives, such as electricity futures and options are used to manage the risk associated with volatility in prices of electricity. This project aims to develop models for pricing electricity derivatives specifically suited for Australia. Because of the non-storable nature of electricity the standard option pricing principle of "no-arbitrage" does not apply to electricity options, such as caps and floors, but applies to options on electricity futures. Therefore a specific model is needed that takes into account the pricing principle of "no-arbitrage" and combines it with other factors that drive electricity prices. The novel element in this proposal is incorporation of the weather forecasts into the models for electricity options. As a result of this study appropriate models for electricity derivatives for various geographical regions in Australia will be developed.Read moreRead less
Analysing Genetic And Environmental Risk Factors And Their Interactions For Common Cancers And Cardiovascular Disease
Funder
National Health and Medical Research Council
Funding Amount
$129,937.00
Summary
The statistical models for analysing cancer and cardiovascular risk factor family data are important for understanding the genetic and environmental aetiology of these diseases, but complicated by the different levels of correlations between relatives in a family. The conventional assumption of independence in observations is invalid in these situations. We intend to develop, test, implement and distribute a comprehensive suite of new statistical methods designed specifically to assistant molecu ....The statistical models for analysing cancer and cardiovascular risk factor family data are important for understanding the genetic and environmental aetiology of these diseases, but complicated by the different levels of correlations between relatives in a family. The conventional assumption of independence in observations is invalid in these situations. We intend to develop, test, implement and distribute a comprehensive suite of new statistical methods designed specifically to assistant molecular geneticists and genetic epidemiologists undertake informative and meaningful analyses of the measured and latent genetic and environmental risk factors and their possible interactions. The two associate investigators, Prof John Hopper and Prof Stephen Harrap, will bring their respective genetic epidemiological and biometric statistical expertise and their prestigious family data resources to this project. With the suite of flexible statistical models and analyses, we will further our knowledge about genetic and environmental risk factors and their interactions of common cancers and major gene effects for cardiovascular phenotypes. Simulation studies will help us understand some phenomena accounted in the research but cannot be replicated in reality and assess the efficiency of the statistical methods and credibility of our analysis results independently. Statistical programs developed in this project can also be used in other genetic and epidemiological studies (e.g. diabetes, epilepsy) where such high-level statistical tools are not yet available.Read moreRead less
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