Currently, all of our training courses are being held online.

All of our courses are hosted by expert certified trainers and research professionals who teach through a mix of demonstrative and practical sessions to provide high-class, practical training.

You can register for our courses online. To discuss any of our courses or specific training requirements, please call +44 (0) 20 8697 3377 .

Climate Econometrics Spring School - 2021

Spring 2021 George Washington University, Washington, D.C. 2.5 days (7th March 2021 - 9th March 2021) OxMetrics

Castle, Doornik and Hendry deliver this new course to our schedule which provides an introduction to the theory and practice of econometric modelling of climate variables in a non-stationary world. It covers the modelling methodology, implementation, practice and evaluation of climate-economic models.

Introduction to Panel Data Analysis with Stata (Online)

25th September & 2nd October, 2020 (CT 9am-11am & 1pm-3pm) Online 2 days (25th September 2020 - 2nd October 2020) Stata

Presented By: Dr. George Naufal (Texas A&M University)

Our web-based 'Introduction to Panel Data Analysis with Stata' course provides an overview of the most-used panel data techniques and is ideal for the beginner/intermediate-level user who wants to learn how to implement panel data estimation with Stata commands.

Introduction to Linear Mixed Models using Stata (online)

30 September - 1 October, 2020 (10am-1pm 2-5pm, London Time) Online 2 days (30th September 2020 - 1st October 2020) Stata

Presented by Sandro Leidi & James Gallagher

This course is running online, via Zoom.

Mixed models are a modern powerful data analysis tool to analyse clustered data, typically arising in studies where the levels of a factor are a random selection from a wider pool, or in the presence of a multi-level nested structure with different levels of variability.

Potential benefits of mixed models are greater generalisability of results and accommodation of missing values. In particular, mixed models have been used in clinical trials to analyse repeated measures, where measurements taken over time naturally cluster according to patient.

The course will illustrate medical and health related applications of mixed modelling, such as multi-centre trials, cross-over trials, and the analysis of repeated measures. The course focuses on the linear mixed model, assuming normally distributed data, and on how to fit it and interpret its results.

Only essential theoretical aspects of mixed models will be summarised.

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