Workshops

Analysis of time-to-event (survival) data

Tuesday 12 and Wednesday 13 September 2017, 9am-5pm

This workshop will be led by Professor Thomas Lumley. He is a professor of Biostatistics at the University of Auckland. He has taught survival analysis at introductory and advanced levels, and has developed software implementations and new methodology.

This two-day workshop will be hosted by the Statistical Consulting Centre in the Department of Statistics at the University of Auckland. The workshop will cover data exploration, data summaries, and regression modelling for time-to-event data. There will be both lecture and practical sessions.

Participants should be familiar with linear and logistic regression, and should bring a laptop with suitable statistical software. R is preferred, but assistance may be available with Stata and SAS.

Registrations are now open. Please click here to learn more and to register.

Introduction to R

Wednesday 19 and Thursday 20 July 2017, 9am-5pm 

The Statistical Consulting Centre will run the following two-day course on Introduction to R. The course presentation will be led

by Kevin Chang.

For more details and booking a spot, please click here

Bayesian and Penalised Regression Methods for Epidemiological Analysis

9am-5pm on Thursday 8 & Friday 9 September, 2016

This course will be led by Professor Sander Greenland, Research Professor and Emeritus Professor of Epidemiology and Statistics at the University of California in Los Angeles.

This short course will be hosted by the Statistical Consulting Centre in the Department of Statistics at the University of Auckland.

To register your interest and to receive further information and notifications, please email Rosemary Barraclough rk.barraclough@auckland.ac.nz or click here.  

For more details and booking a spot, please click here

mixOmics workshop: Multivariate data analysis methods for biological data

9am-5pm on Thursday 9 & Friday 10 April 2015  

The objective of this tutorial is to introduce the fundamental concepts behind multivariate approaches. These approaches are particularly useful for data exploration and integration of biological data in systems biology. Each methodology will be applied on exemplar studies using the R package mixOmic

Two-Day Biostatistics Workshop

Data Monitoring Committees & Interim Analyses in Clinical Trials

Mon & Tues, 23 and 24 February 2015

The course is relevant to all those who need to set up data monitoring committees (DMCs) and work with them throughout the course of a clinical trial.  It is also relevant to those who may serve as members of DMCs. The material in the course is aimed at a mixed audience of statisticians and non-statisticians. It will focus on practical issues around the workings of DMCs including a review of group sequential methods and FDA and CHMP guidance on DMCs. Throughout the course, mock DMC sessions will be convened where various scenarios will be considered and discussed, and decisions have to be made. The different practices in different areas (both medical and geographical), and the complexities that brings for the statisticians will also be discussed.

Design and Analysis of Structured Experiments

Part 2: Unbalanced and Correlated Data

Thurs & Fri, 11 and 12 December 2014 (9am – 5pm)

This two-day course gives an introduction to linear mixed models in the analysis of experiments. We will use  use the software ASReml in R (ASReml-R). The course is aimed at:

(1)   biologists who want to upskill their working knowledge in the analysis of data collected from single- and multi-factor experiments in the presence of nuisance sources of variation, and

(2)   statisticians wanting to learn how to use ASReml-R.

It follows on from the “Part 1 Balanced Data” course “Design and Analysis of Structured Experiments (Balanced Data)”, but can be taken independently by those who have a working knowledge of analysis of experiments. This course will alternate between lectures and practical sessions.

Design and Analysis of Structured Experiments

Part 1:  Balanced Data

Mon & Tues, 8 and 9 December 2014 (9am – 5pm)

This two-day course is aimed at biologists seeking a more formal introduction to the design and analysis of experiments. It will cover the principles of design and analysis of experiments, limiting attention to experiments with balanced data. Both single- and multi-factor treatments will be considered. The material is based on Chapters 1-11 of the new book “Statistical Methods in Biology: Design and Analysis of Experiments and Regression” (Welham et al, September 2014, Chapman & Hall/CRC Press). The course will alternate between lectures and practical sessions, using the R statistical software with the new package aovmixed (due for release December 2014), which implements a general algorithm for balanced designs within the R environment. The aovmixed package provides a wide range of functions for saving and plotting results.