Courses

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 .

Advanced Panel Data Analysis with Stata

23rd - 24th April 2021 Online 2 days (23rd April 2021 - 24th April 2021) Stata

Presented by Dr. Malvina Marchese (Cass Business School, City, University of London)

The course follows the Panel data Analysis with Stata and aims at provide participants with a theoretical and practical understanding of advanced panel methods, i.e. non-linear panel models.

Each session briefly introduces the different methodologies, discussing strengths and weaknesses with a focus on the interpretation of the results. Hands-on sessions with many practical examples and exercises to discuss the different methodologies on panel data analysis.

Regression Models for Categorical and Limited Dependent Variables

06th - 07th May 2021 Online 2 days (6th May 2021 - 7th May 2021) Stata

Presented by Dr. Anis Samet

This workshop is an introduction to regression analysis with categorical dependent variables using the Stata software. It will cover the most commonly used regression models for categorical outcomes: binary logit and probit, ordinal logit, and multinomial logit.

The course assumes that attendees have prior knowledge of common commands in Stata to organize and handle data and undertake standard regression techniques. Nevertheless, this is an introductory course.

How to Write Your Dissertation with Stata

7th May 2021 Online 1 day (7th May 2021 - 7th May 2021) Stata

The aim of this course is to provide participants with an in-depth understanding of how a good MSc dissertation should look, and how to easily use Stata to obtain any required econometrics.

Participants will receive a free temporary Stata license for the duration of the course

The course is meant for any MSc student writing their MSc dissertation, who needs guidance on the best structure, and most suitable econometric methods to apply. No previous knowledge of Stata is required.

Advances in Causal Inference using Stata

14th - 15th May 2021 Online 2 days (14th May 2021 - 15th May 2021) Stata

Presented by: Dr. Giovanni Cerulli

Econometric modelling for causal inference and program evaluation have witnessed a tremendous development in the last decade, with new approaches and methods addressing an expanding set of challenging problems, both in medical and the social sciences. This course covers some recent developments in causal inference and program evaluation using Stata.

It will provide participants with the essential tools, both theoretical and applied, for a proper use of recent micro-econometric methods for policy evaluation and causal modelling in situations where the standard treatment setting poses limitations.

More specifically, the course will focus on these approaches: (i) Difference-in-differences (DID) with time-varying and time-fixed binary treatment; (ii) the Synthetic Control Method (SCM) for program evaluation, suitable when datasets on many times and locations are available; (iii) models for multivalued and quantile treatment effect estimation.

After attending the course, the participant will be able to setting up and managing a correct evaluation design using Stata, by identifying the policy framework, the appropriate econometric method to use interpreting correctly the results. The course will provide various instructional examples on real datasets.

Instrumental Variables and Structural Equation Modelling using Stata - Online

7th - 8th June 2021 Online 2 days (7th June 2021 - 8th June 2021) Stata

Course Overview

Presented by Dr. Giovanni Cerulli

This course provides participants with the essential tools, both theoretical and applied, for a proper use of instrumental variables (IV) and structural equation models (SEM) for statistical causal modelling using Stata.

2021 Stata Summer School

15th - 20th June 2021 Online 6 days (14th June 2021 - 19th June 2021) Stata

Our Stata Summer school provides a very popular and flexible course framework allowing cost-effective attendance at any course separately, or the entire school. This is a great opportunity for students, academics and professionals to expand their econometrics skills and learn how they can apply econometrics and statistics from professionals pioneering research at the forefront of their specialist fields.

For the first time, we will be running our Summer school entirely online, so you can join from the comfort of your home, anywhere in the world.

Live sessions 10.00-12.00; 13.00-15.00; 15.30-17.00 including Q&A

Macroeconomic Density Forecasting & Nowcasting

21st - 22nd June 2021 Online 2 days (21st June 2021 - 22nd June 2021) EViews

Presented By: Dr. Andrea Carriero (Queen Mary, University of London)

Whether you deal with forecasting at a Central Bank, public institution, bank or consultancy firm; or you use forecasting techniques in your research, this is the perfect course to bring you up to date with the latest methods in the forecasting profession.

Causal Inference using Stata

9th August 2021 Online 1 day (9th August 2021 - 9th August 2021) Stata

Presented By: Dr. Austin Nichols

This course is for professionals and researchers from all academic disciplines who wish to improve their use of Stata.

Participants will be introduced to Stata and causal inference using practical examples. The fundamentals of data analysis and visualization will also be taught, using appropriate Stata commands and programming techniques

Introduction to Linear Mixed Models using Stata

23 September - 24 September 2021 Online 2 days (23rd September 2021 - 24th September 2021) 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.

Introduction to Generalised Linear Mixed Models using Stata

27th - 28th September 2021 Online 2 days (27th September 2021 - 28th September 2021) Stata

Presented by Sandro Leidi & James Gallagher

This course is running online, via Zoom.

Mixed models have become increasingly popular, as they have many practical applications. However, the traditional linear mixed model with normally distributed errors may not always be appropriate for modelling discrete response variables, such as binary data and counts. Typically these types of responses are analysed using generalised linear models such as logistic regression and Poisson regression.

Commonly-used generalised linear models will be extended to deal with multiple error structures, using a variety of examples, generally drawn from medical and health related fields. Specific applications, such as repeated measurements and multi-centre trials will also be considered. For example, investigating the presence or absence of adverse events collected in a multi-centre clinical trial.

The emphasis will be on practical understanding, although an outline of the theory will be presented. Practical examples will be used to illustrate the methods, and participants will have the opportunity to fit and interpret models themselves in hands-on computer based practicals.

Note this course does not cover marginal or GEE type models for repeated measurements.

Advanced Machine Learning using Stata - Co-Developed with Lancaster University

25th - 26th October 2021 Online 2 days (25th October 2021 - 26th October 2021) Stata

Presented by Dr. Giovanni Cerulli

This course will focus on three specific techniques: regression and classification trees (including bagging, random forests, and boosting), kernel-based regression, and global methods (step-wise, polynomial, spline, and series regressions).The teaching approach will be mainly based on the graphical language and intuition more so than on algebra. The training will make use of instructional as well as real-world examples, and will evenly balance theory and practical sessions.

The course is open to people coming from all scientific fields, but it is particularly targeted to researchers working in the medical, epidemiological and socio-economic sciences.

Econometrics of Program Evaluation Using Stata

8th & 9th November, 2021 Online 2 days (8th November 2021 - 9th November 2021) Stata

Presented By: Dr. Giovanni Cerulli

This course will provide participants with the essential tools, both theoretical and applied, for a proper use of modern micro-econometric methods for policy evaluation and causal counterfactual modelling under both assumptions of “selection on observables” and “selection on unobservables”. The course will cover these approaches: Regression adjustment (parametric and nonparametric), Matching (on covariates and on propensity score), Reweighting and Double-robust methods, and Difference-in-differences methods.

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