Major Research Projects

• Statistical Methods for Flow Cytometric Data
• Handling Missing Data in Complex Household Surveys
• Efficient Design for Generalized Linear Models
• New methods for small group analysis from sample surveys
• Methodology Development Partnership with Australian Bureau of Statistics
• Sampling for Subpopulations in Household Surveys with Application to Maori and Pacific Sampling
• Collaboration with New Zealand Ministry of Health

Statistical Methods for Flow Cytometric Data

Flow cytometry is a method by which multiple characteristics of single cells or other particles are simultaneously measured as they pass through a laser beam in a fluid stream.

It continues to expand as a tool for medical and biological research, particularly in the areas of immunology, molecular biology, parasitology and haematology. The ability of flow cytomerty to meaure multiple characteristics of cells is a major advantage compared to conventional cell-based arrays, which are limited to recording population averages.

A typical flow cytomerty experiment results in multivariate samples of size about 100,000, corresponding to the number of cells. The porperties of each cell are described by a multi-dimensional vector. Current commercial technology supports dimensions between 3 and 13. Two of the dimensions usually correspond to the intensity of forward scatter and side scatter which characterise the physical properties of the cell (e.g. size and granularity). The remaining dimensions correspond to the intensity of the cell's fluorescence at a given wavelength (colour).

With funding by a Discovery Project from the Australian Research Council, we are developing new statistical methodology to aid flow cytmetric data analysis. Even though the methodology is driven by issues arising in flow cytomerty research, it is mostly generic and applicable to other large multi-dimensional settings. Examples of methodology developed so far include: feature significance for multivariate densities, on generalised linear mixed model ideas.

Outcomes from the grant are regularly posted on the grant's website

Handling Missing Data in Complex Household Surveys

Household surveys are a widely used methodology in research, government and industry. These surveys are affected by missing data at a variety of levels, such as time points within person, people within households and households within areas. This project will create methods which deal with missing data incorporating these complex multi-level structures. For more details of this project, (HandlingMissingData.pdf) click here.

The project is funded by an ARC Linkage Proposal, with industry partner the Australian Bureau of Statistics. The total funding from the ARC and the ABS is $103,950 over three years. The chief investigators are Dr Robert Clark and Professor Ray Chambers. A PhD student, Luise Lago, commenced work on the project in July, 2007.

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Efficient Design for Generalized Linear Models

In industrial, commercial and social research, we collect data in order to predict the outcome of a process based on the inputs to that process. We want to maximize the information that is gained from the data. Good planning is crucially important to achieve this. This project will determine how best to select the inputs to the process for many situations that occur in research. A computer package to answer these questions will be written. The nation will benefit from a fundamental increase in efficiency of research and, therefore, in efficient use of research dollars.

The chief investigators are A/Prof KG Russell; Prof JA Eccleston; Prof SM Lewis; Dr DC Woods. The project has received funding of $164,000 from 2006 - 2008.

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New methods for small group analysis from sample surveys

Ray Chambers and David Steel are chief investigators on this linkage project with industry partners are Australian Bureau of Statistics, Australian Bureau of Agricultural and Resource Economics, and the Centre for Epidemiology and Research, Public Health Intelligence in NZ Ministry of Health.

Total funding $601,000.

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Methodology Development Partnership with Australian Bureau of Statistics

The pressing need to establish a program of research into new and innovative methods of collecting, analysing and exploiting statistical information has led to the Australian Bureau of Statistics (ABS) partnering with the University of Wollongong (UOW) to establish a Chair in Statistical Methodology.

Professor Ray Chambers commenced in this position in May 2006, following a distinguished career as Director of the Southampton Statistical Sciences Institute at the University of Southampton in the UK.

UOW Vice-Chancellor, Professor Gerard Sutton (left) with Australian Statistician, Mr Dennis Trewin, from the Australian Bureau of Statistics (ABS)

The Australian Statistician, Mr Dennis Trewin, said the agreement would forge stronger links between the ABS and the university sector and ensure that statistical methodology skills are available more widely around the nation. "Statistical methodology is an area of critical importance to the ABS and other providers of statistics. It requires specialist training to ensure quality statistics are produced for Australia. It is increasingly important in the information age and there is need for more people with these skills," he said.

Recent activities as part of this partnership include:

• A series of one-day Fellows Research Meetings (insert link here) held at Goulburn has been established. "Goulburn 4" was held in July 2007, and Goulburn 5 is planned for November 2007. This meetings are hosted by UoW, and include a range of researchers and statisticians from UoW, the ABS, the Australian Bureau of Research Economics and other government departments and universities.
• UoW has conducted annual symposiums at the ABS since 2005.
• UoW has presented a number of short courses at the ABS including Survey Estimation, Principles and Practices of Methodological Research and Logistic Regression.
• ABS managers and statisticians have visited UoW for a number of visits, to discuss research plans, statistical issues at the ABS and to plan joint activities.
• A mentoring scheme has been established where UoW academic statisticians provide technical leadership and mentoring for selected ABS staff.

An ARC Linkage project on "Handling Missing Data in Complex Household Surveys" commenced in July 2007, with industry partner the ABS. An ARC Linkage project on "New Methods for Small Group Analysis" was approved in 2007 and will commence shortly. The industry partners for this project are the ABS, the Australian Bureau of Agricultural and Resource Economics, and the Centre for Epidemiology and Research, Public Health Intelligence in NZ Ministry of Health.

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Sampling for Subpopulations in Household Surveys with Application to Maori and Pacific Sampling

This project will be completed in 06/07 by a project team consisting of Robert Clark (CSSM, lead investigator), Robert Templeton (NZ Ministry of Health), Mike Doherty (Statistics New Zealand) and Angela Forbes (Statistics New Zealand). The project has been funded by the Statistics New Zealand Official Statistics Research Fund with a budget of NZD$69,100.

Many NZ national household surveys have a requirement to produce statistics with adequate precision both for the whole of NZ and for important subpopulations, particularly the Maori and Pacific populations. Two strategies for achieving this are: geographically-based unequal probability sampling (usually based on Census data); and screening (where part of the sample are initially screened, and only members of the subpopulation of interest are eligible for the full survey). Methods and theory are available for determining how to combine screening and unequal probability sampling. However, these methods do not allow for multi-stage sampling which is used in most household surveys, or for the inaccuracies resulting from using Census data to apply to periods in between Censuses. This project will develop new theory and methods to address these shortfalls, and apply them to the NZ context. The use of the Maori electoral roll will also be evaluated, including a clerical coverage assessment. The outcomes of the project will include: improved cost efficiency for NZ surveys where subpopulation estimates are a priority; more precise Maori and Pacific statistics; and a better understanding of sample design for subpopulations in NZ and in the international surveys and statistical community.

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Collaboration with New Zealand Ministry of Health

The Public Health Intelligence Unit of the New Zealand Ministry of Health (MoH) and the CSSM signed a two year collaboration agreement including funding of up to NZ$225,000, in October 2006.

Signing the agreement are UOW Vice-Chancellor, Professor Gerard Sutton and the Deputy Director General, NZ Ministry of Health, Dr Don Matheson (right) watched on by Dr Barry Borman, Manager, Public Health Intelligence, NZ Ministry of Health; UOW Deputy Vice-Chancellor, Professor Margaret Sheil; CSSM Director, Professor David Steel; and CSSM Deputy Director, Dr Robert Clark

The partnership includes a range of training activities and statistical projects. Projects to date include:

• Development of the sample design for the 2006-2007 New Zealand Health Survey;
• Development of preliminary sampling weights for the New Zealand Health Survey;
• Sample design and analysis advice on other surveys including the NZ Alcohol and Drug Use Survey, the NZ Oral Health Survey and the NZ Adult Nutrition Survey.

CSSM has presented short courses in Wellington to MoH and other researchers and policy analysts including:

• Sample Design and Estimation for Household Surveys (two day course, October 2005)
• Interpreting Survey Data (session as part of Public Health Intelligence Workshop, May 2006)
• Survey Quality and Cost (one day course, September 2006)
• Logistic Regression (one day course April 2007)
• Multilevel Modelling (two day course, planned for December 2007)

Activities planned for 2008 include a scholarship program, and further expansion of the statistical training programme.

For more information on the New Zealand Health Survey sample design, see the (Clark and Gerritsen Symposium Proceedings Submission.pdf) attached paper which was presented at the Statistics Canada Symposium in November 2006.