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 .

Time Series Analysis & Modelling Using Stata

11th - 12th February 2021 (London time 3pm - 11pm) Online 2 days (11th February 2021 - 12th February 2021) Stata

Presented By: Dr George Naufal (Public Policy Research Institute (PPRI), Texas A&M University)

Time series data are nowadays collected for several phenomena in social and empirical sciences. Initially collected at year or quarter level, time series data are now used by marketing analytics, financial technology, and other fields in which data are collected at much smaller intervals (daily, hourly and even by the minute). This course focuses on the fundamental concepts required for the analysis, modelling and forecasting of time series data and provides an introduction to the theoretical foundation of time series models alongside a practical guide to the use of time series analysis techniques implemented in Stata 16. The course is based on the textbook by S. Boffelli and G. Urga (2016), Financial Econometrics Using Stata, Stata Press Publication.

Panel Data Econometrics - Co-Developed with Lancaster University

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

Prof. Sébastien Laurent, Aix-Marseille University

Panel data econometrics has developed rapidly over the last decades.

Longitudinal data are more and more available to researchers and methods to analyse these data are in high demand from scholars from different fields.

The course offers a comprehensive overview on panel data methods with Stata, covering static and dynamic linear models.

Each session briefly introduces the different methodologies, discussing strengths and weaknesses with a focus on the interpretation of the results.

By the end of the two-day on-line course, participants should be able to prepare panel data for the analysis with Stata, choose the relevant model, get the parameter estimates and interpret the results.

Instrumental Variables and Structural Equation Modelling using Stata - Online

1st - 2nd March 2021 Online 2 days (1st March 2021 - 2nd March 2021) Stata

Course Overview

Presented by Dr. Giovanni Cerulli

Course Timetable: 10am - 12pm & 2pm - 4pm

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.

Econometrics of Program Evaluation Using Stata

8th & 9th March, 2021 (10am - 12pm & 2pm - 4pm, London time) Online 2 days (8th March 2021 - 9th March 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.

An Introduction to Panel Data Analysis using Stata

26th - 27th March 2021 Online 2 days (26th March 2021 - 27th March 2021) Stata

Presented By: Dr. Malvina Marchese (CASS Business School, London)

Course Timetable: 10am - 12pm & 2pm - 4pm

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.

An Introduction to Machine Learning using Stata - In collaboration with Lancaster University

7th - 8th April, 2021 Online 2 days (7th April 2021 - 8th April 2021) Stata

Presented by Dr. Giovanni Cerulli

Course Timetable: 10am - 12pm & 2pm - 4pm (London time)

This course is a primer to machine learning techniques using Stata. Stata owns today various packages to perform machine learning which are however poorly known to many Stata users. This course fills this gap by making participants familiar with (and knowledgeable of) Stata potential to draw knowledge and value from rows of large, and possibly noisy data. The teaching approach will be based on the graphical language and intuition more than on algebra. The training will make use of instructional as well as real-world examples, and will balance evenly theory and practical sessions.

Data Science For Health Researchers: An Introduction to Stata

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

Overview

Presented by: Dr. Vincent O'Sullivan

Course Timetable: 10am - 12pm & 2pm - 4pm

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.

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)

Course Timetable: 10am - 12pm & 2pm - 4pm

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.

Advances in Causal Inference using Stata (Online)

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

Presented by: Dr. Giovanni Cerulli

Course Timetable: 10am - 12pm & 2pm - 4pm

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

Course Timetable: 10am - 12pm & 2pm - 4pm

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.

An Introduction to Linear Mixed Models using Stata (online)

23 September - 24 September, 2021 (10am-1pm 2-5pm, London Time) 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.

Advanced Machine Learning using Stata - In collaboration with Lancaster University

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

Course Timetable: 10am - 12pm & 2pm - 4pm

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.

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