Courses and Training
Read more about courses and training run by members of the Child Health Informatics Group.
Upcoming/current courses
| Course name | Where | Dates | Description |
|---|---|---|---|
| Introduction to ECHILD: Linked data from health, education and childrens social care | Online | Ongoing | The course is aimed at both analysts intending to use ECHILD and researchers who want to understand more about how the data can be used for policy relevant research. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice learning how to analyse and interpret ECHILD data using R or Stata. For more information and to register please see: https://instats.org/seminar/introduction-to-echild-education-and-ch3 |
| RADIANCE (Rigorous Training in Longitudinal Data Science) | Online | Ongoing | RADIANCE (Rigorous Training in Longitudinal Data Science) is a UKRI funded project that provides online training in data science to quantitative researchers involved with biomedical and social data. The training is offered for free at all levels, from introduction to key concepts, to intermediate courses, to more advanced topics such as programming, machine learning and causal inference courses. Other courses include using administrative data for research, regression modelsand addressing Causal Questions using Real World Data. RADIANCE also offers on-line one-to-one clinics where researchers can have individual targeted support from a RADIANCE instructor, following attendance to modules and short courses. For more information, please see: https://radiance.org.uk/training/ and to be the first to hear when registration to modules and courses opens please follow us on Twitter @Radiance_Data. |
Past courses
Click here to see historic courses
Course name | Where | Dates | Description |
Introduction to ECHILD: Linked data from health, education and childrens social care | In person at University College London, UK | 25/03/2024 - 26/03/2024 | The course is aimed at both analysts intending to use ECHILD and researchers who want to understand more about how the data can be used for policy relevant research. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice learning how to analyse and interpret ECHILD data using R or Stata. For more information and to register please see: https://store.southampton.ac.uk/short-courses/school-of-economic-social-and-political-sciences/national-centre-for-research-methods/introduction-to-echild-linked-data-from-health-education-and-childrens-social-care |
Introduction to Hospital Episode Statistics | Online | 21/02/2024 - 22/02/2024 | This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data. By the end of the course participants will:
The course is for researchers and data analysts in academia, government and private sector at all levels who are using or planning to use HES for their work. For more information please see: https://store.southampton.ac.uk/short-courses/school-of-economic-social-and-political-sciences/national-centre-for-research-methods/ncrm-introduction-hospital-episode-statistics-online |
Short-course: causal inference in practice | In person at University College London, UK | 14/02/2024 - 16/02/2024 | This course introduces some of the most popular tools from causal inference and gives practical explanations about how to apply these methods to real research questions. The course will cover potential outcomes, target trial emulation, propensity score-based methods, instrumental variable analysis, and mediation analysis. Each approach will be explained within the causal inference framework, along with the recommended sensitivity analyses, to assess the plausibility of the results. To attend, please express your interest: here. |
Introduction to Hospital Episode Statistics | Online | 12/10/2023 - 13/10/2023 | This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data. By the end of the course participants will:
The course is for researchers and data analysts in academia, government and private sector at all levels who are using or planning to use HES for their work. For more information please see: https://www.ucl.ac.uk/child-health/events/2023/oct/introduction-hospital-episode-statistics |
Introduction to Data Linkage | University of London | 13/09/23 -14/09/23 | This short course is designed to give participants a practical introduction to data linkage and is aimed at both analysts intending to link data themselves and researchers who want to understand more about the linkage process and its implications for analysis of linked data—particularly the implications of linkage error. Day 1 will focus on the methods and practicalities of data linkage (including deterministic and probabilistic approaches) using worked examples. Day 2 will focus more on analysis of linked data, including concepts of linkage error, how to assess linkage quality and how to account for the resulting bias and uncertainty in analysis of linked data. Examples will be drawn predominantly from health data, but the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice. For more information and registration please visit: https://www.ncrm.ac.uk/training/show.php?article=12944 |
Introduction to Hospital Episode Statistics | Online | 11/05/2023 - 12/05/2023 | This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data. By the end of the course participants will:
The course is for researchers and data analysts in academia, government and private sector at all levels who are using or planning to use HES for their work. For more information please see: https://www.ncrm.ac.uk/training/show.php?article=12237 |
Introduction to Data Linkage | In person at UCL. | 15/03/2023 - 16/03/2023 | This short course is designed to give participants a practical introduction to data linkage and is aimed at both analysts intending to link data themselves and researchers who want to understand more about the linkage process and its implications for analysis of linked data—particularly the implications of linkage error. Day 1 will focus on the methods and practicalities of data linkage (including deterministic and probabilistic approaches) using worked examples. Day 2 will focus more on analysis of linked data, including concepts of linkage error, how to assess linkage quality and how to account for the resulting bias and uncertainty in analysis of linked data. Examples will be drawn predominantly from health data, but the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice. For more information and booking, please visit: https://www.ncrm.ac.uk/training/show.php?article=12273 |
Introduction to Hospital Episode Statistics | Online | 03/10/2022 –14/10/2022 | This course will provide you with an understanding of how HES data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. The course is for researchers and data analysts in academia, government and private sector at all levels who are using or planning to use HES for their work. By the end of the course you will be able to: Understand how and why HES data are collected; Be aware of the strength and weaknesses of using HES data for research; Be able to implement basic cleaning, management and analysis tasks using HES data; and Know how to ensure anonymity and confidentiality when using HES. For more information and booking, please visit: https://www.ucl.ac.uk/child-health/events/2022/oct/introduction-hospital-episode-statistics |
Joining-up our understanding of causal inference: Similarities and differences across the econometrics and biostatistics literature | Online | Part 1: Dec 2021 - Feb 2022 Part 2: May 2022 to June 2022 | “Correlation is not causation” is a common refrain used when empirical evidence is presented. Despite this, most clinical, epidemiological, and public health investigations attempt to address causal questions. Motivated by these needs, extensive methodological research especially over the last 20 years has made substantial advances in formalizing how to move beyond correlations. This series of workshops will introduce modern causal inference methods, making reference to both the econometrics and biostatistics literature. We will discuss the potential outcome framework and learn how to draw and interrogate causal diagrams; we will translate causal questions into causal estimands and compare methods for their |
Online | 19/05/2022 - 20/05/2022 | This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data. | |
Online | 21/10/2021 - 22/10/2021 | This short course will provide you with an understanding of how HES data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. | |
National Centre for Research Methods | 19/05/2020 - 20/05/2020 | This short course is designed to give participants a practical introduction to data linkage and is aimed at both analysts intending to link data themselves and researchers who want to understand more about the linkage process and its implications for analysis of linked data—particularly the implications of linkage error. Day 1 (Introduction to Data Linkage) will cover examples of the uses of data linkage, data preparation, and methods for linkage (including deterministic and probabilistic approaches). Day 2 (Introduction to Analysing Linked Data) will cover processing of linked data, concepts of linkage error and bias, and handling linkage error in analysis. Examples will be drawn predominantly from health data but the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice. | |
National Centre for Research Methods | 03/10/2019 - 04/10/2019 | This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data. | |
Introduction to Hospital Episode Statistics | UCL GOS Institute of Child Health | 13/06/2019 - 14/06/2019 | Hospital Episode Statistics (HES) is the national hospital admission database for England, which is increasingly being used for research, clinical outcomes monitoring, and public health and service planning. This course will provide you with an understanding of how HES data are collected and coded, their structure, and how to clean and analyse HES data. |
National Centre for Research Methods | 01/04/2019 - 02/04/2019 | This short course is designed to give participants a practical introduction to data linkage and is aimed at researchers either intending to use data linkage themselves or those who want to understand more about the process so that they can analyse linked data. Day 1 (Introduction to Data Linkage) will cover examples of the uses of data linkage, data preparation, and methods for linkage (including deterministic and probabilistic approaches and privacy-preserving linkage). Day 2 (Introduction to Analysing Linked Data) will cover processing of linked data, concepts of linkage error and bias, and handling linkage error in analysis. The main focus of this course will be health data, although the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice. | |
Introduction to Hospital Episode Statistics | UCL GOS Institute of Child Health | 07/01/2019 - 08/01/2019 | Hospital Episode Statistics (HES) is the national hospital admission database for England, which is increasingly being used for research, clinical outcomes monitoring, and public health and service planning. This course will provide you with an understanding of how HES data are collected and coded, their structure, and how to clean and analyse HES data |
National Centre for Research Methods | 19/05/2020 - 20/05/2020 | This short course is designed to give participants a practical introduction to data linkage and is aimed at both analysts intending to link data themselves and researchers who want to understand more about the linkage process and its implications for analysis of linked data—particularly the implications of linkage error. Day 1 (Introduction to Data Linkage) will cover examples of the uses of data linkage, data preparation, and methods for linkage (including deterministic and probabilistic approaches). Day 2 (Introduction to Analysing Linked Data) will cover processing of linked data, concepts of linkage error and bias, and handling linkage error in analysis. Examples will be drawn predominantly from health data but the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice. | |
National Centre for Research Methods | 03/10/2019 - 04/10/2019 | This course will provide participants with an understanding of how Hospital Episode Statistics (HES) data are collected and coded, their structure, and how to clean and analyse HES data. A key focus will be on developing an understanding of the strengths and weaknesses of HES, how inconsistencies arise, and approaches to deal with these. Participants will also learn how to ensure individuals’ anonymity and confidentiality when carrying out analyses and publishing results based on HES. The course consists of a mixture of lectures and practicals for which participants will use Stata software to clean and analyse HES data. | |
Introduction to Hospital Episode Statistics | UCL GOS Institute of Child Health | 13/06/2019 - 14/06/2019 | Hospital Episode Statistics (HES) is the national hospital admission database for England, which is increasingly being used for research, clinical outcomes monitoring, and public health and service planning. This course will provide you with an understanding of how HES data are collected and coded, their structure, and how to clean and analyse HES data. |
National Centre for Research Methods | 01/04/2019 - 02/04/2019 | This short course is designed to give participants a practical introduction to data linkage and is aimed at researchers either intending to use data linkage themselves or those who want to understand more about the process so that they can analyse linked data. Day 1 (Introduction to Data Linkage) will cover examples of the uses of data linkage, data preparation, and methods for linkage (including deterministic and probabilistic approaches and privacy-preserving linkage). Day 2 (Introduction to Analysing Linked Data) will cover processing of linked data, concepts of linkage error and bias, and handling linkage error in analysis. The main focus of this course will be health data, although the concepts will apply to many other areas. This course includes a mixture of lectures and practical sessions that will enable participants to put theory into practice. | |
Introduction to Hospital Episode Statistics | UCL GOS Institute of Child Health | 07/01/2019 - 08/01/2019 | Hospital Episode Statistics (HES) is the national hospital admission database for England, which is increasingly being used for research, clinical outcomes monitoring, and public health and service planning. This course will provide you with an understanding of how HES data are collected and coded, their structure, and how to clean and analyse HES data |