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.
Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identi ....Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identifying RNA molecules that contribute to quantitative phenotypes including susceptibility to disease. As such, it will directly benefit fundamental science via the discovery and classification of new molecules. Indirectly, it will lead to breakthroughs in biology, and consequently to major medical and pharmaceutical advances in the diagnosis and treatment of genetic disease.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.
Discovery Early Career Researcher Award - Grant ID: DE200100425
Funder
Australian Research Council
Funding Amount
$409,364.00
Summary
Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advance ....Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advanced analytical methods to perform this integration and dissection of the biological consequences of non-random mating in humans at an unprecedented phenotypically detailed scale. The benefit of this project will be to identify new drivers of mate choice that can contribute to economic, health and social inequalities. Read moreRead less
Genomic selection: a new frontier for higher rates of genetic gain in wheat. The historical rates of genetic gain in wheat production are insufficient to meet the world's future needs for wheat-based food. Genomic selection (GS) is the most likely candidate tool that is capable of delivering the required level of genetic gain. This project will develop data-sets and statistical methods to implement GS in wheat.