Pre-Registration form

invited speakers

who should
attend

call for papers

OZCOTS 2010

workshops

venue and
location

travel

accommodation

social program

sponsorship opportunities

expression of interest

contact us

home

 

Workshops

A series of pre and post conference workshops, ranging from 1-5 days in duration will support the conference.

More information including workshop costs will be advised shortly.

Workshop topics include:

Topics in Clinical Trials

DATES: 4-5 December 2010

Presenters: Scott Evans, Senior Research Scientist, Harvard School of Public Health and Rui Wang, Instructor of Medicine, at the Massachusetts General Hospital and Harvard Medical School.

A clinical trial is the gold standard scientific study for evaluating the efficacy and safety of an intervention. Several challenges arise during the design, conduct, analyses, and reporting of clinical trials. This lecture-based short-course will address several topic areas in clinical trials. The course will cover topics such as: (1) general issues in clinical trial design, (2) the design, conduct, analyses, and reporting of non-inferiority trials, (3) data monitoring committees and associated processes, (4) benefit:risk analyses and reporting, (5) using prediction to make more informed decisions during interim analyses, (6) subgroup analyses and personalized medicine, (7) Meta analysis, and (8) the roles of the clinical trial statistician.

For more information on this workshop, download the workshop information flyer or contact Dr Mark Griffin on m.griffin@uq.edu.au.

Register your interest in attending this workshop.

 

Capture-Recapture Models Using Mark and other Software for Fisheries and Wildlife Research

DATES: 1-5 December 2010

Presenters: Professor Ken Pollock, Murdoch University and Dr Lyndon Brooks, Southern Cross University.

Kenneth H. Pollock has been appointed to a chair in Quantitative Methods in the Fisheries Center at Murdoch University. Previously he was a professor at North Carolina State University in Statistics, Biomathematics and Biology specializing in quantitative methods for fisheries, wildlife and conservation biology. He is an elected fellow of the American Statistical Association. The position is funded by FRDC, Western Australia Fisheries and Murdoch University. One component of this position is to develop and present workshops on quantitative methods for fisheries and other natural resource postgraduate students and professional scientists.

Outline:

  • Introduction to Capture-Recapture Models

  • Closed Population Models

    • Modelling abundance

    • Modelling unequal catchability due to time, behaviour and heterogeneity among individuals

  • Open Population Models

    • Estimating survival and movement for open populations

    • Estimating abundance and recruitment for open populations

  • Combining Closed and Open Population Models

    • Pollock's Robust Design

    • Unequal capture probabilities

    • Unobservable states and temporary emigration

    • The Open Robust Design Model 

  • Conclusions and Future Directions

  • Software Used Mark, Capture, Popan.  We will get into sophisticated modelling by the end of the week  so some previous use of Mark even if limited would be an advantage.

For more details on this workshop please contact Ken Pollock; phone 08 9360 6582. For more information consult the website.

return to top of page

 

Introductory Analysis of Linked Health Data

DATES: 29 November to 3 December 2010

Location: School of Population Health, The University of Western Australia

Places limited to 36.

This intensive five-day course, developed by Professor D'Arcy Holman, covers the theory and practical skills needed to analyse linked data from administrative, clinical and research databases at the introductory to intermediate level. In particular, it includes: i) an overview of the theory of data linkage systems and methods, ii) principles of epidemiologic measurement and methods applicable to linked data covering disease trends and health care utilisation and outcomes, iii) minimising sources of measurement error, iv) statistical analyses on longitudinal linked health data, v) conceptualisation and management of large linked data files, and vi) writing computing syntax to prepare linked data files for analysis and production of results from statistical procedures in SPSS, SAS or Stata (the course supports all three).

Basic familiarity with computing syntax and a working knowledge of statistical concepts, including regression models, used in data analysis in the medical and social sciences is assumed.

A computing laboratory will be provided, but many participants prefer to bring their own notebooks supporting either SPSS, SAS or Stata.

Course Coordinators: Professor D'Arcy Holman and Associate Professor David Preen
Please visit the School of Population Health website for full course information.

return to top of page

 

Advanced Analysis of Linked Health Data

DATES: 13 to 17 December 2010

Location: School of Population Health, The University of Western Australia

Places limited to 36.

Developed by Professor D'Arcy Holman, this is an intensive five-day course that provides researchers with the opportunity to build on their pre-existing theoretical knowledge and skills in the analysis of linked health data by exploring advanced topics, including: i) high-level understanding of methods for valid estimation of effect measures and outcomes based on complex, multi-sourced linked data sets, ii) complex longitudinal research designs and their implementation, iii) case distribution designs and their implementation in medication safety research, iv) analysis of linked mortality, institutional, pharmaceutical and primary care health data, and v) computing syntax to prepare complex linked data files for analysis and production of results from advanced statistical procedures in SPSS, SAS or Stata (the course supports all three).

The course assumes a level of knowledge comparable to Introductory Analysis of Linked Health Data. Familiarity with syntax writing and knowledge of statistical concepts (at an introductory or intermediate level) used in biostatistical analysis is also required.

A computing laboratory will be provided, but many participants prefer to bring their own notebooks supporting either SPSS, SAS or Stata.

Course Coordinators: Professor D'Arcy Holman and Associate Professor David Preen
Please visit the School of Population Health website for full course information.

return to top of page

 

Introduction to R  

DATE: Friday 10 December 2010

R is a free and extremely powerful software environment for statistical computing, data analysis, and graphics. It has become the tool of choice for many statisticians. The R environment is highly flexible and extensible, and it contains a wealth of functions to carry out standard and non-standard statistical and graphical analyses. 

The course will consist of an alternating series of lectures and computer practicals. Topics covered will include:

  • Introduction to the R software system and its syntax

  • Linear and generalized linear models in R

  • R Graphics

It is designed for statisticians and statistical practitioners who have little or no experience with R.

The course presenters are Martin Hazelton (Chair of Statistics, Massey University New Zealand) and Berwin Turlach (A/Professor of Statistics, University of WA). Both are experienced users of R, and use it in their research, teaching, and consulting.

return to top of page

 

Analysing spatial point patterns in R

DATE: Saturday 11 December 2010

Presenter: Adrian Baddeley, CSIRO/University of Western Australia

Data which record the spatial locations of events (such as crimes, disease cases, meteorite impacts) or objects (trees, nests, galaxies, cells) can be regarded as a spatial pattern of points. This workshop presents statistical methodology for analysing spatial point patterns, and its practical implementation in the statistical package R.  The workshop is based on 'spatstat', an add-on library for spatial statistics in R.

The workshop will feature theoretical presentations, software demonstrations and hands-on practical exercises. Participants should bring a laptop for the exercises.

Topics covered include:

  • statistical formulation and methodological issues

  • data input and handling

  • exploratory analysis

  • nonparametric intensity estimation

  • distance methods and summary statistics such as Ripley's K function

  • point process models (Poisson, Gibbs, Cox, cluster)

  • likelihood, pseudolikelihood and Bayesian inference

  • model validation

  • simulation techniques

  • multitype and marked point patterns

return to top of page


PLATINUM PLUS
SPONSOR:


PLATINUM SPONSOR:

 

SILVER SPONSORS:

 

 

 

BRONZE SPONSORS: