Beginning in April 2024, we will start recording our seminars for archival on our website. Each video will be accompanied by the R code, data sets, and pdf files of the presentations. You will also have access to a dedicated Discussion Board where you can ask any seminar-related questions.

For a one-time fee of 25 GBP, you will receive unlimited access to all seminar materials, including those from past events, current sessions, and future presentations, for as long as the seminars are conducted. This fee is to help cover the costs associated with hosting and streaming the video content.

Payment: Credit card only.

The following videos are currently available:

• Data exploration and visualisation. Date: 22 April 2024.
  • Video duration: 2 hours and 30 minutes.
  • We covered key tools for detecting outliers and collinearity in data. Additionally, we explored methods to visualise relationships and dependencies. Furthermore, we explained why creating histograms of the data can be a waste of time. These are the steps that you need to apply before analysing your data.
  • R code and data for one fully worked-out example are provided.
• Analysing proportional data using beta and ordered beta GLM. Date: 5 August 2024.
  • Video duration: 2 hours and 20 minutes.
  • We started by providing a concise explanation of the beta distribution and the ordered beta distribution. Following that, we illustrated how both distributions could be applied within a Generalised Linear Model (GLM) to analyse proportional data, such as coverage. Additionally, we demonstrated how the ordered beta distribution could be effectively used to analyse proportional data that includes zeros and ones.
  • R code and data for two fully worked out examples (beta GLM and ordered beta GLMM) are provided.
• What is a Tweedie GLM? Date: 2 September 2024.
  • Video duration: 1 hours and 56 minutes. 
  • We explained the concept of the Tweedie distribution and demonstrated the application of a Tweedie generalised linear model (GLM) to continuous (lobster biomass) data.
  • R code for a simulation study is provided. R code and data for one fully worked-out example are provided.
• What is a linear mixed-effects model? 11 November 2024.
  • Video duration: 1 hour and 59 minutes.
  • We explored subjects like pseudo-replication, random effects, and mixed models, along with topics such as the number of clusters and the number of observations per cluster. Mixed models, also known as mixed-effects models, incorporate both fixed effects (covariates), and random effects. This approach allows for the analysis of complex data with multiple layers of variability, making it particularly useful in studies where data are collected from different groups or time points.
  • R code and data for one fully worked-out example are provided.

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