We are happy to announce the 76th (2024) Annual General Meeting (AGM), to be followed by the Lancaster Lecture given by Dr. Gordana Popovic. The event will be held at 4:30PM (AEDT), March 28th at the University of New South Wales, Sydney, Anita B. Lawrence Centre (previously Red Centre), Room 4082. We hope to see you all there!

The materials for the 2024 AGM will be progressively added here.

You can find the 2023 AGM minutes here.  

Any questions, please feel free to contact: secretary.nswbranch@statsoc.org.au.

Date:  Thursday, 28th March 2024
Time:
4:30pm - 5:30pm: AGM
5:30pm - 6:00pm: Break and refreshments
6:00pm - 7:00pm: Lancaster Lecture
7:00pm onwards: Dinner (at a nearby restaurant). See RSVP section below

Venue: Room 4082, Anita B. Lawrence Centre (previously Red Centre), UNSW or via zoom.

RSVP: Please register via SSA NSW: 2024 AGM + Lancaster Lecture if you are attending the AGM and the Lancaster Lecture in person. Attending the dinner requires a separate RSVP and please register prior to the event. 

Lancaster Lecture

Title : Odds-On Favorite: Analysing haphazard Surveys with mild-ish Assumptions

Speaker: Dr Gordana Popovic

Abstract: 

While statisticians generally recommend collecting data via probability sampling, applied researchers studying humans frequently use haphazard and other non-probability samples to conduct surveys, and statistical consultants are regularly asked to help analyse such data. Principled analysis of non-probability samples relies on having reference data from probability samples or censuses, to adjust for non-response bias by say weighting or covariate adjustment. What can be done without auxiliary information?

It is well known that odds ratios are invariant under certain types of selection bias, for example outcome dependent sampling, which is why we use them in case control studies. We extend these results to selection bias on both the outcome and predictor, by way of some assumptions about how these biases are related.

In a collaboration on racial bias in police searches from a haphazard Facebook survey, where no auxiliary data was available, we used these assumptions to estimate odds ratios. We discuss how the assumptions were communicated with researchers so that their plausibility could be assessed by domain experts.

Gordana completed her PhD in statistics and statistical ecology at UNSW in 2007, and has been working as a statistical consultant at Stats Central, UNSW Sydney every since. Her focus is on mentoring junior applied researchers to take a principled approach to quantitative research though teaching and collaboration.