Online course with on-demand video and live Zoom meetings:
Introduction to GAM and GAMM using frequentist tools
This online course consists of 5 modules representing a total of approximately 40 hours of work. Each module consists of multiple video files with short theory presentations, followed by exercises using real data sets, and video files discussing the solutions. All video files are on-demand and can be watched online, as often as you want, at any time of the day, within a 6 month period.
A discussion board allows for daily interaction between instructors and participants. The course also contains 5 2-hour live web meetings (using Zoom) in which we summarise the theory and the exercises. Attending these live web meetings is optional. We will run the web meetings in different time zones. These Zoom summary sessions will be recorded and you can watch them on the course website. You can also use a Discussion board to ask any questions on the course material. The course fee includes a 1-hour face-to-face video chat with the instructors. You can use this video chat to ask questions about your own data.
A detailed outline of the course is provided below. All exercises consist of a data set, a video describing the data and the questions, R solution code, and a video discussing the R solution file.
We start with a short revision of data exploration and linear regression. We then introduce generalised additive models (GAM) to model non-linear relationships. We will execute these models in mgcv.
In Module 2, we will revise linear mixed-effects models and show how to implement a generalised additive mixed-effects model (GAMM). We also show how to include an interaction between a smoother and a categorical covariate.
In Module 3, we will revise basic GLMs and extend these towards GAMs. In Modules 4 and 5 we will discuss GAMMs for the analysis of count data, absence-presence data, proportional data, and continuous data. We also discuss 2-dimensional smoothers (including the soap-film smoother for study areas with barriers; e.g. an island in the sea).
Keywords: Gaussian, Poisson, negative binomial, gamma, Tweedie, Bernoulli, binomial and beta GAM and GAMM. Hierarchical GAMM. Important changes in smoothers. Univariate smoothers and 2-dimensional smoothers. Barriers and soap-film smoothers.
Access to the course website is for 12 months.
Free 1-hour face-to-face video meeting: The course fee includes a 1-hour face-to-face video meeting with one or both instructors. The meeting needs to take place within 12 months after the last live zoom meeting. You can discuss your own data but we strongly suggest that the statistical topics are within the content of the course. The 1-hour needs to be used in one session and will take place on a mutually convenient day and time of the day.
Web meetings: Web meetings are hosted on zoom.us. Click here for recommended internet speed (see the text under 'Recommended bandwidth for Webinar Attendees'). We will record the meetings and make them available on the course website.
Discussion Board: You can use the Discussion Board to ask any questions related to the course material.
Pre-required knowledge: You need to have good knowledge of R, data exploration, and linear regression. Working knowledge of Poisson, negative binomial, Bernoulli GLM, and mixed-effects modelling is recommended, but revision exercises will be provided. This is a non-technical course.
Cancellation policy: What if you are not able to participate? Once participants are given access to course exercises with R solution codes, pdf files of certain book chapters, pdf files of PowerPoint or Prezi presentations and video solution files, all course fees are non-refundable and non-transferable to another participant.
Copyright: Sharing the access details of the course website or the pdf files of our course material is prohibited. Video files cannot be downloaded, but they can be watched in the same way as on Netflix.