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 .

Data Science For Health Researchers: An Introduction to Stata

15th - 16th April 2021 Online 2 days (15th April 2021 - 16th April 2021) Stata


Presented by: Dr. Vincent O'Sullivan

This course is for professionals and researchers who are new to Stata. The course assumes only limited statistical knowledge and experience of using statistical software. The participants will be introduced to Stata’s interface. They will be shown how manage and prepare datasets for analysis. The fundamentals of data analysis and visualization will also be taught. Then, the participants will be introduced to two of the main data analysis tools: linear regression and logistic regression. Participants will be taught the statistical theory behind these methods, and they will apply these methods to specially chosen datasets using examples from health research.

Machine Learning for Prediction and Causal Inference - Masterclass

20th - 21st April, 2021 Online 2 days (20th April 2021 - 21st April 2021) Stata

Presented By: Dr. Melvyn Weeks (University of Cambridge)

This course will review the application of machine learning techniques to both prediction problems and so-called causal problems where a firm or policy maker needs to understand the impact of some form of intervention on a heterogeneous population. We contrast a modelling approach where the analyst makes certain assumption on model specification, including functional form, with an approach where the data mechanism is presumed unknown. In this context we consider the econometrician’s concern for internal validity, alongside the focus within machine learning of ensuring that a model is robust in the sense of generalising to unseen data (external validity).

The course will focus upon topics at the intersection of machine learning and econometrics, covering a mix of theory and applications. In making the distinction between models which are used to solve a prediction problem and models which are used to estimate some form of causal effect, we introduce participants to identification strategies in econometrics. In covering two broad areas where machine learning is used, namely prediction, classification and causal effects, for each case we link the exposition to parametric bench- marks. For Machine Learning models in prediction, classification and causal effects we provide examples using Stata, R and Python.

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 Introduction to Panel data Analysis with Stata and aims to 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.

Vector Autoregression (VAR) Modelling using EViews (Online)

26th - 27th April 2021 Online 2 days (26th April 2021 - 27th April 2021) EViews

Presented by Prof. Lorenzo Trapani (University of Nottingham)

The course offers an intermediate/advanced level overview of stationary VARs, cointegrated VARs and the VECM, and an introduction to Structural VARs (SVARs). It is a mixture, with equivalent weights, of methodology and practice, and each session is complemented by a data example. The SVAR part is also based on discussing several examples which are commonly encountered in macroeconometrics and monetary economics.

The course is aimed at practitioners and applied researchers in general who wish to either have a comprehensive introduction to the practical use of VARs and their variants, or a more rigorous understanding of these tools.

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.

An Introduction to Model Building Techniques in Stata

12th May 2021 Online 1 day (12th May 2021 - 12th May 2021) Stata

Presented by Robert Grant

In healthcare, economics or commercial data science, analysts of all backgrounds have to build models for their data. Models help us to understand causal relationships and forecast the future, but as statistician George Box put it, "all models are wrong, but some are useful". How do you know if your models are useful? Or maybe even wrong? This one-day course is an introduction to the techniques used in model building.

Advances in Causal Inference using Stata

13th - 14th May 2021 Online 2 days (13th May 2021 - 14th 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.

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

18th - 19th May 2021 Online 2 days (18th May 2021 - 19th May 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.

Building Your Own Models In EViews

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

Presented by Dr. Malvina Marchese

This course is for economists, econometricians and applied researchers who want to go even further in EViews by coding something that is not implemented in the existing routines such as long memory GARCH models or Value at Risk. In addition, one may wish to make life easier and to ask EViews to perform some repetitive tasks. This is where EViews Programming starts. The goal of this training course is to make life easier, namely to do things with only a small investment instead of learning a completely new language.

This course will be running online, as a Zoom webinar.

Midas Touch: Advanced Time Series In EViews

25th - 26th May 2021 Online 2 days (25th May 2021 - 26th May 2021) EViews

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

This course offers a comprehensive discussion of advanced time series models in EViews and their applications to a wide range of fields including: financial econometrics and macro econometrics. The course offers both a theoretical discussion of the models and many practical applications to time series data.

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.

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