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.
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.
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
The role of households, neighbourhoods and networks in social statistics. Many issues affect the social progress of the country. Social research can determine the factors affecting issues such as unemployment, poverty, educational attainment, crime victimization and poor health. Survey and other data are used extensively to examine these conditions and their association with attributes of people. This project will provide methods to better determine the impact of effects associated with the h ....The role of households, neighbourhoods and networks in social statistics. Many issues affect the social progress of the country. Social research can determine the factors affecting issues such as unemployment, poverty, educational attainment, crime victimization and poor health. Survey and other data are used extensively to examine these conditions and their association with attributes of people. This project will provide methods to better determine the impact of effects associated with the household structure and other groups and social networks. The improved ability to assess the impact of these factors will have economic and social benefits. These benefits will arise from improved analysis leading to better decisions and improvements in the design of research studies improving their cost efficiency.Read moreRead less
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.
Modelling the Choices of Individuals. Individuals make decisions daily and some of these decisions have wide-reaching and long-term consequences, such as choices among housing, public transport, electoral candidates and health care options. The principal aim of this project is to develop reliable and valid ways to model individual level choice processes. Once completed, this will provide insights into ways to aggregate sampled observations when population-level applications are required, and all ....Modelling the Choices of Individuals. Individuals make decisions daily and some of these decisions have wide-reaching and long-term consequences, such as choices among housing, public transport, electoral candidates and health care options. The principal aim of this project is to develop reliable and valid ways to model individual level choice processes. Once completed, this will provide insights into ways to aggregate sampled observations when population-level applications are required, and allow us to compare and test several competing theories of choice behaviour. This will enable us to make contributions to understanding and modelling human decision making in many fields ranging from marketing to medicine.Read moreRead less
Enhancing social research in Australia using dual-frame telephone surveys. The growing surge in mobile phones and mobile-phone only households has had a significant impact on the representativeness of social surveys and accuracy of social outcome measures. This project will develop methods for generating sampling lists of both types of telephone numbers to improve population coverage and accuracy of outcome measures.
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.