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Events listing - SSA events

To have your event added to this list, please forward the event details, including url, to our Events Coordinator Jodi Phillips.

Upcoming events

    • 6 Feb 2025
    • 9:30 AM - 5:00 PM
    • School of Public Health and Preventive Medicine Conference Rooms, Monash University School of Public Health and Preventive Medicine, 553 St Kilda Road Melbourne, VIC 3004

    The Monash University Methods in Evidence Synthesis Unit invites you to Evolving Methods for Evidence Synthesis of Health Research: Symposium 2025.

    Start the new year with an in-person symposium and learn about the latest developments and evaluation of methods for evidence synthesis of health research across a range of review types and stages of the review process. It’s designed for anyone who undertakes evidence synthesis or has an interest in the development and evaluation of methods for evidence synthesis.

    National and international guest speakers will join for a series of plenary presentations exploring:

    the use of artificial intelligence (AI) in reviews

    safeguarding the integrity of research when using individual participant data

    rethinking which meta-analysis model is best for most systematic reviews

    how we can improve the reporting of systematic reviews

    All presentations will be pitched for an audience with general knowledge about evidence synthesis methods.

    The symposium finishes at 5pm, but don’t miss our social event from 5.30 onwards at the Commons Collective, just a few minutes walk from our conference venue.

    Registration: Register here

    Standard in-person: $150

    Student in-person: $125



    • 6 Feb 2025
    • 12:00 PM
    • 3 Apr 2025
    • Online- Weekly 1 hour meetings taking place Thursdays
    • 8
    Registration is closed

    The Social Research Centre and the Statistical Society of Australia (SSA) are very proud to offer statistical training from the International Program in Survey and Data Science (IPSDS), a joint program of the University of Mannheim and the Joint Program in Survey Methodology at the University of Maryland.

    Places are limitedplease register early to take advantage of early bird discounts and secure a place.

     Topics:

    1. Introduction; Course Perspectives

    2.  Simple Random Sampling, Sampling Frames, and Introduction to Clustering

    3. Stratified Sampling I

    4. Stratified Sampling II, Systematic selection

    5. Cluster Sampling

    6. Unequal-Sized Clusters I

    7. Unequal-Sized Clusters II

    8. Variance Estimation

    Timeframe:

    February 6 – April 3, 2025. Weekly Meetings taking place Thursdays, 12:00 – 1:00 pm AEDT


    Course Objectives

     By the end of the course, participants will… ▪ understand the basic ideas, concepts and principles of probability sampling from an applied perspective ▪ be able to identify and appropriately apply sampling techniques to survey design problems ▪ be able to compute the sample size for a variety of sample designs ▪ understand and be able to assess the impact of the sample design on survey estimates ▪ be able to estimate the precision of the survey statistics using different estimation techniques


    Your instructor: Raphael Nishimura, PhD 

    Raphael Nishimura is the Director of Sampling Operations in Survey Research Operations at the Survey Research Center (SRC) in the Institute of Social Research of the University of Michigan. He has been working with sampling and survey statistics for over ten years. He holds a PhD in survey methodology from the University of Michigan and a bachelor’s degree in statistics from the University of São Paulo. His main research interest includes sampling methods, survey nonresponse and adaptive/responsive designs. Nishimura is also the director of the Sampling Program for Survey Statisticians of the SRC Summer Institute for Survey Research Techniques


    Prerequisites

     The course is presented at an intermediate statistical level. While we will not develop mathematical aspects of sampling theory, statistical notation and outlines of some algebraic proofs will be given. A sound background in applied statistics, proficiency in mathematics, including basic algebra, is necessary, since some algebraic derivations will be presented (although little emphasis will be placed on the derivations). A thorough understanding of the notation and algebraic results will be required.



    Grading will be based on:

    8 Homework assignments (50% of grade)

    ▪ 8 Quizzes (one at the start of each online session; 15% of grade)

    ▪ Participation in discussion during the weekly online meetings, submission of questions in the weekly discussion forum, demonstrating understanding of the required readings and video lectures, and positive contributions on the Discussion Forum, see below (10% of grade)

    ▪ A final open-book online exam (25% of grade)

    Early Bird Deadline
    Please book before 6 January 2025 to take advantage of the Early Bird Deadline.

    Prices include GST.

    Disclaimer

    Participants will receive access data for the online course, in particular to any learning platform that may be used. The rights of use connected to the access data are personally assigned to the participant. Passing on the access data is not allowed. Also, the temporary transfer to third parties is not permitted.
    The right to use the transmitted access data, in particular with regard to any materials or video recordings provided, can only be exercised up to a maximum of 2 months after the program end. After expiration of this 2-months period, the access data will be deleted by Mannheim Business School (MBS). Before the expiration of this period, the participant may view the respective recorded course as often as desired and without time restriction.
    If we have reasons to believe that the participant is abusing the right of use granted to him or that there is a violation of the terms of use, MBS reserves the right to change the participant’s access data as well as to partially or completely block the access or to prohibit the further use of the digital content.

    Group bookings

    For group bookings, please email events@statsoc.org.au with the names, email addresses, and telephone numbers  of the participants in the group.

    Cancellation Policy
    Occasionally courses have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.

    Cancellations received prior to two weeks before the event will be refunded, 
    minus the  Stripe processing fee (1.75% + $0.30 per transaction) and an SSA administration fee of $20. 

    From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au.

    For any questions, please email events@statsoc.org.au

    • 7 Feb 2025
    • 9:00 AM - 4:30 PM
    • School of Public Health and Preventive Medicine Conference Rooms, Monash University School of Public Health and Preventive Medicine, 553 St Kilda Road Melbourne, VIC 3004

    The Monash University Methods in Evidence Synthesis Unit invites you to Assessing the risk of bias in non-randomised studies evaluating the effects of interventions | In-person workshop

    Date and time: Friday 7 February 2025 from 9am to 4.30pm

    Location: School of Public Health and Preventive Medicine Conference Rooms, Monash University School of Public Health and Preventive Medicine, 553 St Kilda Road Melbourne, VIC 3004

    Registration: Register here

    Standard in-person: $490

    Student in-person: $350

    Non-randomized studies of interventions (NRSI) can provide evidence additional to that available from randomized trials about long term outcomes, rare events, adverse events and populations that are typical of real-world practice. However, limitations in the design, conduct, analysis and reporting of an NRSI may lead to underestimation or overestimation of the true effects of an intervention, which is known as bias. Therefore, a critical aspect when interpreting results from an NRSI is assessing whether features of the study may have placed the results at risk of bias, thus making them less trustworthy. The ROBINS-I (Risk Of Bias In Non-randomized Studies – of Interventions) tool provides a structured process for researchers to make risk-of-bias judgements. The tool is the gold standard approach for assessing the risk of bias in NRSI, is widely used (the 2016 version has been cited >13,000 times), and has been endorsed by Cochrane for use in their systematic reviews. A new version of ROBINS-I that incorporates several improvements and innovations will be launched in early 2025, together with an online implementation that will facilitate its use.

    Who is this workshop for and what does it cover?

    This in-person workshop on how to assess the risk of bias in NRSI is designed for those undertaking systematic reviews, synthesizing evidence for guidelines, or generally interested in learning how to appraise studies.

    The presenters will describe key features of version 2 of the ROBINS-I tool for cohort studies in which intervention groups are allocated during the course of usual treatment decisions. We will highlight the updates and improvements to the original (2016) version of the tool and show how it has been implemented in online software for use by review authors. The workshop involves a mix of presentations, interactive discussions and hands-on exercises. Electronic copies of the slides will be provided on the day of the workshop. 

    Any questions? Please email Matthew Page at matthew.page@monash.edu

    • 10 Feb 2025
    • 9:00 AM
    • 14 Feb 2025
    • 12:30 PM
    • Online for 3 mornings: Mon/Wed/Fri

    This course, conducted by the Statistical Consulting Centre, is suitable for researchers who need to fit mixed models to their data. Mixed models are also known as multi-level models or hierarchical models, and include cluster randomised trials in medicine, unbalanced designs in agriculture, hierarchical structures in education, repeated measures in the social sciences, and nested factors in ecology. Topics include fixed and random effects; variance components; nested and crossed factors; comparison and adjustment of means; models with categorical and continuous predictors; using R to fit mixed models; interpretation of R output.

    To register:

    https://scc.ms.unimelb.edu.au/statistics-courses/course-listing/mixed-models


    • 24 Feb 2025
    • 28 Feb 2025
    • Deakin University’s Melbourne CBD campus 727 Collins Street, Docklands VIC 3008

    Deakin Epidemiology is pleased to offer a summer Masterclass focused on Logistic regression to be delivered by arguably the world’s most famous teacher of this statistical technique – Prof. Stanley Lemeshow. In years past, Lemeshow together with Ken Rothman offered back-to-back masterclasses in Biostats and Epi in Tasmania which were a bit of an institution, with many epidemiologists and biostatisticians building their knowledge and networks by heading south for a healthy dose of upskilling or as a refresher. Stan has agreed to offer this program onshore once again in Australia, this time at Deakin University’s Melbourne CBD campus 727 Collins Street, Docklands VIC 3008.

    This 5-day course (Feb 24-28, 2025) will provide theoretical and hands-on practical knowledge and skills in statistical modeling with an in-depth focus on logistic regression analysis – the standard method for regression analysis of binary, multinomial and ordinal response data in health research. Each day comprises a 4-hr class in the morning and a 2-hr practical session in the afternoon and opportunities to network with fellow health and medical practitioners and researchers.”

    Places are limited, so get in early! For more information click here!


    • 25 Feb 2025
    • 12:00 PM - 1:00 PM
    • Online
    Register

    Statistical Computing and Visualisation section proudly presents the Di Cook Award webinar, promoting open-source statistical software development. 

    There were many excellent submissions in this round. Come along to hear from this year's winner Xiaolei (Adam) Wang for his work on the bsvarSIGNs package. This software implements state-of-the-art algorithms for the Bayesian analysis of Structural Vector Autoregressions identified by sign, zero, and narrative restrictions.

    We will also be hosting some lightning talks from other notable entries!

    • 27 Feb 2025
    • 28 Feb 2025
    • Peter Hall Building, University of Melbourne

    This workshop, conducted by the Statistical Consulting Centre, covers the tools needed to efficiently work with data using R, particularly focusing on importing, rearranging, describing and visualising data. It is suitable for beginners and those familiar with R who are looking to improve their skills and strategies for working with data in a reproducible manner.

    This workshop covers the tools needed to efficiently work with data using R, particularly focusing on importing, rearranging, describing and visualising data. It is suitable for beginners and those familiar with R who are looking to improve their skills and strategies for working with data in a reproducible manner.

    The workshop is presented by Cameron Patrick and Sandy Clarke-Errey in person at the University of Melbourne over two days, with a mixture of lecture presentations and practical work.

    The course covers the following topics:

    • the basics of R and RStudio;
    • using R Markdown to tie together your R code, output and analytical decisions;
    • the benefits of a reproducible approach to data analysis;
    • concepts relating to types of data and how to best organise the data you collect;
    • importing data from commonly used file formats including Excel and CSV;
    • practical data-cleaning tasks to get your original data ready for analysis;
    • methods for summarising and describing data;
    • producing high-quality graphics with the ‘ggplot’ package;
    • presenting results from statistical analyses in tables and graphs.

    More details and registration here: https://scc.ms.unimelb.edu.au/statistics-courses/course-listing/research-and-r


    • 11 Mar 2025
    • 12:30 PM - 1:30 PM
    • online
    Register

    Personal Journey Of Len Cook: A Webinar by Early Career & Student Statisticians Network and History Standing Committee of SSA.

    This is the fourth in the series of webinars that focus on the personal journey of older Australian statisticians who have made a difference. 

    This is the first in the series that focuses on the personal journey of a New Zealand statistician. The interview of Len, for up to 40 minutes, will be conducted by Dennis Trewin, former SSA President and a member of its History Committee. There will then be a Q&A led by Muskaan, the facilitator for the New Zealand branch of the ECSSN.