Principal speaker
Associate Professor Sama Low-Choy
Other speakers
Dr Clair Alston-Knox
In this two-part series (Parts 1 and 2), we aim to develop your ability to critically understand and evaluate the results of a linear or logistic regression, produced in either a classical or Bayesian setting, and hence interpret output from standard statistical software and in published studies. Although you will gain hands-on experience doing logistic regression in your preferred software package (with support here for either R or Autostat), the emphasis will be on interpreting the outputs, which can be obtained using many different packages.
In this way, we guide you to develop basic statistical literacy skills in explanatory or predictive modelling using linear or logistic regression. In addition, we share techniques for eliciting and encoding prior information into statistical distributions. These not only consolidate and test your understanding of the regression models, they also prepare a foundation for many useful skills in: capturing the current state of knowledge before data is collected using an expert model (a prior predictive); preparing for the next study via modern techniques for design (e.g. simulations for sample size analysis); updating the current state of knowledge about effects (via priors in a Bayesian regression); or consolidating multiple sources of information via a classical meta-analysis (of effect sizes).
Event categories
RSVP
RSVP on or before Monday 18 November 2019 , by email RED@griffith.edu.au , or by phone 0755529107 , or via http://events.griffith.edu.au/d/zhqpzb/4W