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Generalised Linear (MIXED) (GLMM), Nonlinear (NLGLM) And General Additive Models (MIXED) (GAMM) (GNAM01)

25 May 2020 - 29 May 2020

£275.00 - £560.00

Course Overview:

This course provides a general introduction to nonlinear regression analysis, covering major topics including, but not limited to, general and generalized linear models, generalized additive models, spline and radial basis function regression, and Gaussian process regression. We approach the general topic of nonlinear regression by showing how the powerful and flexible statistical modelling framework of general and generalized linear models, and their multilevel counterparts, can be extended to handle nonlinear relationships between predictor and outcome variables. We begin by providing a comprehensive practical and theoretical overview of regression, including multilevel regression, using general and generalized linear models. Here, we pay particular attention to the many variants of general and generalized linear models, and how these provide a very widely applicable set of tools for statistical modeling. After this introduction, we then proceed to cover practically and conceptually simple extensions to the general and generalized linear models framework using parametric nonlinear models and
polynomial regression. We will then cover more powerful and flexible extensions of this modeling. framework by way of the general concept of basis functions. We’ll begin our coverage of basis function regression with the major topic of spline regression, and then proceed to cover radial basis functions and the multilayer perceptron, both of which are types of artificial neural networks. We then move on to the major topic of generalized additive models (GAMs) and generalized additive mixed models (GAMMs), which can be viewed as the generalization of all the basis function regression topics, but cover a wider range of topic including nonlinear spatial and temporal models and interaction models. Finally, we will cover the powerful Bayesian nonlinear regression method of Gaussian process regression.

Intended Audience

This course is aimed at anyone who is interested to learn and apply nonlinear regression methods. These methods have major applications throughout the economics and other social sciences, life sciences, physical sciences, and machine learning.

Venue – PS statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map

Availability – 20 places

Duration – 5 days

Contact hours – Approx. 28 hours

ECT’s – Equal to 3 ECT’s

Language – English


• COURSE ONLY – Includes lunch and refreshments and welcome meal Monday evening.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, refreshments and welcome dinner Monday evening. Self-catering facilities are available in the accommodation. Accommodation is multiple occupancy (max 3- 4 people) single sex en-suite rooms. Arrival Sunday 24th May (between 17:00-21:00) and departure Friday 29th May (accommodation must be vacated by 09:15).

To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.

Other payment options are available please email oliverhooker@psstatistics.com

PLEASE READ – CANCELLATION POLICY: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@psstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees (and accommodation fees if booked through PS statistics) will be credited. However, PS statistics will not be held responsible/liable for any travel fees, accommodation costs or other expenses incurred to you as a result of the cancellation. Because of this PS statistics strongly recommends any travel and accommodation that is booked by you or your institute is refundable/flexible and to delay booking your travel and accommodation as close the course start date as economically viable.

Dr. Mark Andrews

Teaching Format
Course Programme


25 May 2020
29 May 2020
£275.00 - £560.00


PS statistics head office
53 Morrison Street
Glasgow, Scotland, G5 8LB United Kingdom
+ Google Map


10 available
16 available