Short course prerequisites

To ensure our courses are suitable for you, and that you can fully benefit from online participation, we identify a number of course prerequisites. We kindly request that you check you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites prior to booking.

Please select a course from the list below to view prerequisites, IT requirements and recommendations. If your course is not listed there are no specific prerequisites.

3D Printing in Congenital Heart Diseases

Please ensure you meet the following prerequisites before booking:

Eligibility	This course is available to University of Bristol staff and postgraduate researchers only. Candidates must be able to fully attend the course and provide feedback.
Conditions	Pilot courses are extremely popular and all live sessions must be attended in full. You should only book onto this course if you are able to commit to attending in full and have time to provide detailed feedback. Attendance is monitored. Failure to attend in full, without a valid reason, will result in your access to pilot course materials being rescinded and you will not be permitted to attend any further pilot courses within the same academic year.
Knowledge	Basic knowledge of 3D printing to the level of our Introduction to Medical 3D Printing short course and an interest in Congenital Heart Diseases.
Software	Segmentation software will be provided. No prior experience is required (users will be guided as part of the course).

Advanced Mendelian Randomization

Please ensure you meet the following prerequisites before booking:

Knowledge	The course is an advanced level course in Mendelian randomization and assumes that participants already have knowledge of the basics of MR. Participants should have completed the Mendelian Randomization short course (or equivalent) and should have experience of conducting MR analyses. Practical sessions will be conducted using R and so participants should have an understanding of using R for data analysis, however previous experience of conducting MR estimation using R is not required.
Software	Practical sessions will be conducted in R and so participants should have a recent version R installed prior to the start of the course. See R Installation Instructions for help getting set up. An online version of R with the required packages for the course pre-installed will be made available to participants to use if they wish for the duration of the course through Posit cloud.

Knowledge

The course is an advanced level course in Mendelian randomization and assumes that participants already have knowledge of the basics of MR. Participants should have completed the Mendelian Randomization short course (or equivalent) and should have experience of conducting MR analyses.

Practical sessions will be conducted using R and so participants should have an understanding of using R for data analysis, however previous experience of conducting MR estimation using R is not required.

Software

Practical sessions will be conducted in R and so participants should have a recent version R installed prior to the start of the course. See R Installation Instructions for help getting set up. An online version of R with the required packages for the course pre-installed will be made available to participants to use if they wish for the duration of the course through Posit cloud.

Advanced Multiple Imputation Methods to deal with Missing Data

Please ensure you meet the following prerequisites before booking:

Knowledge	Prior attendance of the Multiple Imputation for Missing Data short course (or equivalent introductory course to missing data concepts and multiple imputation) or be familiar with the concept of multiple imputation, and have used it in practice. Also, familiarity with directed acyclic graphs (DAGs) and standard regression methods for continuous and binary outcomes beyond a basic level.
Software	You must have a recent version of Stata* or R installed in advance of the course. We recommend running this through RStudio Desktop or Posit Cloud. Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week). Go to R Installation Instructions for help getting set up. *A link to create an account and access Posit Cloud will be provided.
Recommendation	For the computer practicals, we recommend that participants either have access to the use of two screens or the ability to print materials in advance of the course.

Analysis of Repeated Measures

Please ensure you meet the following prerequisites before booking:

Knowledge	You must be familiar with the algebra of standard regression models for continuous outcomes (to beyond the standard of the short course Introduction to Linear and Logistic Regression Models or to the level implied by module 3 of the Centre for Multilevel Modelling online multilevel modelling course).
Software	You must be familiar with R or Stata. The course will run mainly in R and some Stata material will be provided, but this is not available for all lectures. Those using Stata* must have this installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. However if you are a student, Stata offer a short term free Student licence (one week).

Knowledge

You must be familiar with the algebra of standard regression models for continuous outcomes (to beyond the standard of the short course Introduction to Linear and Logistic Regression Models or to the level implied by module 3 of the Centre for Multilevel Modelling online multilevel modelling course).

Software

You must be familiar with R or Stata. The course will run mainly in R and some Stata material will be provided, but this is not available for all lectures.

Those using Stata* must have this installed in advance of the course.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata. However if you are a student, Stata offer a short term free Student licence (one week).

Causal Inference in Epidemiology: Concepts and Methods

Please ensure you meet the following prerequisites before booking:

Knowledge	Applicants must have knowledge and experience of a variety of regression models, including Cox models for time-to-event data, and their implementation in Stata or R. Such knowledge must be to beyond the level achieved in the Introduction to Linear and Logistic Regression Models course. We recommend that you do not attend this course in the same year that you have attended Introduction to Linear and Logistic Regression Models
Software	You must have a recent version of Stata* or R installed in advance of the course. We recommend running this through RStudio Desktop or Posit Cloud*. Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week). **A link to create an account and access Posit Cloud will be provided.

Knowledge

Applicants must have knowledge and experience of a variety of regression models, including Cox models for time-to-event data, and their implementation in Stata or R. Such knowledge must be to beyond the level achieved in the Introduction to Linear and Logistic Regression Models course. We recommend that you do not attend this course in the same year that you have attended Introduction to Linear and Logistic Regression Models

Software

You must have a recent version of Stata* or R installed in advance of the course. We recommend running this through RStudio Desktop or Posit Cloud**.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

**A link to create an account and access Posit Cloud will be provided.

Co-Design, Co-Production and Participatory Action Research

Please ensure you meet the following prerequisites before booking:

Recommendations	We will ask course participants to familiarise themselves with the NIHR Guidance on co-producing a research project, alongside some short videos, before attending the course so that we can maximise sharing and discussion time in the course. The link to the NIHR guidance is here: https://www.learningforinvolvement.org.uk/content/resource/nihr-guidance-on-co-producing-a-research-project/

Essentials of Infectious Disease Modelling and Economic Evaluation

Please ensure you meet the following prerequisites before booking:

Software	Access to a laptop or desktop computer for the duration of the course (joining by mobile/ tablet would be insufficient). This course requires use of R through Posit Cloud. You will need to set up a free Posit Cloud account, instruction for which can be found on our R Installation Instructions page.
Recommendation	Although the computer practicals will be in the programming language R, no knowledge of R is assumed.

Software

Access to a laptop or desktop computer for the duration of the course (joining by mobile/ tablet would be insufficient).

This course requires use of R through Posit Cloud. You will need to set up a free Posit Cloud account, instruction for which can be found on our R Installation Instructions page.

Recommendation

Although the computer practicals will be in the programming language R, no knowledge of R is assumed.

Further Survival Analysis

Please ensure you meet the following prerequisites before booking:

Knowledge	Participants should be familiar with the basics of survival analysis, to at least the level attained from the Introduction to Rates and Survival Analysis short course.
Software	Participants should be familiar with using Stata statistical software and implementing survival analyses within Stata (code for practicals will also be made available in R). You must have Stata or R installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

Knowledge

Participants should be familiar with the basics of survival analysis, to at least the level attained from the Introduction to Rates and Survival Analysis short course.

Software

Participants should be familiar with using Stata statistical software and implementing survival analyses within Stata (code for practicals will also be made available in R).

You must have Stata or R installed in advance of the course.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

Genetic Epidemiology

Please ensure you meet the following prerequisites before booking:

Knowledge	Prior experience of genetic epidemiology is not required, but we encourage participants to familiarise themselves with some of the genetic terminology and concepts before the course. To help you to do this we have produced a series of 3 short videos (specifically for this course) which provide a background to basic genetics for those of you who are new to the subject. We recommend you watch these before coming on the course. In addition the following resources both contain some good basic information: https://en.wikipedia.org/wiki/Genetics http://www.dorak.info/genetics/ This course will require students to use analytical software in a command-line Linux and R environment. We will include all instructions but do recommend that you have some experience of these computer environments before the course.
Software	During the course, you will run all computer practicals on your own computer/laptop using Posit Cloud (formerly known as RStudio Cloud) which allows you access to the R and Linux environments. We will briefly introduce the Cloud in the first practical and provide all main code for all practicals. You do not need to install any software packages yourself. The operating system can be either Windows or Mac.
Recommendation	You should consider having a fast internet speed for synchronous/live sessions and for practicals. We would also recommend the use of two screens for practicals. Please note this is an intensive 5 day full time course.

Healthcare Systems Resilience: Analysing Failure, Driving Change, and Sustaining Improvement

Please ensure you meet the following prerequisites before booking:

Eligibility

This course is available to University of Bristol staff and postgraduate researchers only. Candidates must be able to fully attend the course and provide feedback.

Conditions

Pilot courses are extremely popular and all live sessions must be attended in full. You should only book onto this course if you are able to commit to attending in full and have time to provide detailed feedback.

Attendance is monitored. Failure to attend in full, without a valid reason, will result in your access to pilot course materials being rescinded and you will not be permitted to attend any further pilot courses within the same academic year.

Intermediate Economic Evaluation Using R

Please ensure you meet the following prerequisites before booking:

Knowledge	Experience with R to level of Chapter 2 of the R for Health Technology Assessment textbook (available for free at https://gianluca.statistica.it/books/online/r-hta/chapters/03.software/software) will be assumed, but a recap will be given of more advanced topics of functions and program flow. Knowledge of cost-effectiveness analysis, specifically on Markov models, will be assumed. Attendees will be expected to read the cohort Markov models in Chapter 9 of the R for Health Technology Assessment textbook (https://gianluca.statistica.it/books/online/r-hta/chapters/10.markov_models/markov-models) in advance of the course, or be comfortable with the material.
Software	You must have R (version 4.1.0 or higher) and RStudio (version 2025.05.1 or newer) installed in advance of the course. Go to R Installation Instructions for help getting set up.
Recommendation	Use of two screens is preferable but not essential.

Knowledge

Experience with R to level of Chapter 2 of the R for Health Technology Assessment textbook (available for free at https://gianluca.statistica.it/books/online/r-hta/chapters/03.software/software) will be assumed, but a recap will be given of more advanced topics of functions and program flow.

Knowledge of cost-effectiveness analysis, specifically on Markov models, will be assumed. Attendees will be expected to read the cohort Markov models in Chapter 9 of the R for Health Technology Assessment textbook (https://gianluca.statistica.it/books/online/r-hta/chapters/10.markov_models/markov-models) in advance of the course, or be comfortable with the material.

Software

You must have R (version 4.1.0 or higher) and RStudio (version 2025.05.1 or newer) installed in advance of the course. Go to R Installation Instructions for help getting set up.

Recommendation

Use of two screens is preferable but not essential.

Introduction to Data Visualisation and Web Applications Using R

Please ensure you meet the following prerequisites before booking:

Knowledge	Course participants should either have attended the Introduction to R course or be familiar with R and/or RStudio. This course is not intended for people who have never used R before.
Software	This course will use Posit cloud. Participants will not need to install the desktop version of RStudio to complete the course. If course participants would like to use RStudio Desktop (Open Source version) alongside the cloud version, this is compatible with Windows, Mac and Linux and is freely available from: https://rstudio.com/products/rstudio/download/ Go to R Installation Instructions for help getting set up. You will also need software able to open and view .pdf (e.g. Adobe Reader) and .docx files (e.g. MS Word).
Recommendation	Participants may find it helpful to have 2 screens. However, this is not a requirement.

Introduction to Economic Evaluation

Please ensure you meet the following prerequisites before booking:

Knowledge	No previous experience or knowledge of economics is required.
Software	Course attendees will need access to a recent version of Excel to complete some of the practical sessions.
Recommendation	To make the best of the course, the use of two screens, or the ability to print materials in advance is advised.

Introduction to Linear and Logistic Regression Models

Please ensure you meet the following prerequisites before booking:

Knowledge	You should have knowledge of statistical methods and their implementation in Stata of at least the level achieved in the Introduction to Statistics short course or in R of at least the level achieved in the Introduction to R short course.
Software	Students should have experience using either R or Stata You must have Stata (version 15 or higher)* installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. However if you are a student, Stata offer a short term free Student licence (one week). For those who would like to work with R during the practical sessions, we will be using Posit Cloud as an interface for R. You can use your own desktop version of R, if you are already familiar/comfortable with this, or we will provide a link to Posit Cloud. Go to R Installation Instructions for further information.
Recommendation	You may find it helpful to have access to two screens - or ability to print materials in advance - in order to run analyses while having course materials open. This is not essential, however.

Knowledge

You should have knowledge of statistical methods and their implementation in Stata of at least the level achieved in the Introduction to Statistics short course or in R of at least the level achieved in the Introduction to R short course.

Software

Students should have experience using either R or Stata

You must have Stata (version 15 or higher)* installed in advance of the course.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata. However if you are a student, Stata offer a short term free Student licence (one week).

For those who would like to work with R during the practical sessions, we will be using Posit Cloud as an interface for R. You can use your own desktop version of R, if you are already familiar/comfortable with this, or we will provide a link to Posit Cloud. Go to R Installation Instructions for further information.

Recommendation

You may find it helpful to have access to two screens - or ability to print materials in advance - in order to run analyses while having course materials open. This is not essential, however.

Introduction to Medical 3D Printing

Please ensure you meet the following prerequisites before booking:

Eligibility

This course is available to University of Bristol staff and postgraduate researchers only. Candidates must be able to fully attend the course and provide feedback.

Conditions

Introduction to Network Meta-Analysis

Please ensure you meet the following prerequisites before booking:

Knowledge	Experience of pairwise meta-analysis (to the level covered by the course Introduction to Systematic Reviews and Meta-analysis), understanding of statistical methods including logistic regression (to the level of the course Introduction to Linear and Logistic Regression Models), and basic experience with R.
Software	You must have R (version 4.2 or higher) and RStudio installed in advance of the course. This course will use RStudio Desktop (Open Source version). This is compatible with Windows, Mac and Linux and is freely available from: https://rstudio.com/products/rstudio/download/ Go to R Installation Instructions for help getting set up in advance of the course starting.
Recommendation	We recommend the use of two screens, to follow the worksheets whilst working in practical computing sessions. However, this is not essential.

Introduction to Protocol Writing

Please ensure you meet the following prerequisites before booking:

Recommendation	It is helpful to attend Introduction to Research Governance prior to taking this course.

Introduction to Qualitative Evidence Synthesis Methods

Please ensure you meet the following prerequisites before booking:

Knowledge	Prior training in and/or experience of qualitative methods are not absolutely required, but will be an advantage.
Recommendation	Two screens will be useful but not essential.

Introduction to Qualitative Research Methods

Please ensure you meet the following prerequisites before booking:

Software	The course includes a session on qualitative software management using NVivo software as an example. NVivo access is not required for the session but is recommended in order to engage with the self-guided workbook.
Other	The course includes preparatory work for live sessions that will enable engagement with workshops and support learning. It is expected this work is completed in attendees own time. The ethnography session includes time to conduct observations in a community setting, e.g. a coffee shop. If possible please complete this day of the course from a location that will allow you to take part in this exercise.

Software

The course includes a session on qualitative software management using NVivo software as an example. NVivo access is not required for the session but is recommended in order to engage with the self-guided workbook.

Other

The course includes preparatory work for live sessions that will enable engagement with workshops and support learning. It is expected this work is completed in attendees own time.

The ethnography session includes time to conduct observations in a community setting, e.g. a coffee shop. If possible please complete this day of the course from a location that will allow you to take part in this exercise.

Introduction to R

Please ensure you meet the following prerequisites before booking:

Software	We will be using Posit Cloud as an interface for R in the practical sessions. You can use your own desktop version of R, if you are already familiar/comfortable with this, or we will provide a link to Posit Cloud. Go to R Installation Instructions for further information.
Recommendation	We recommend using two screens, or a large enough screen, that will allow you to complete practical work alongside viewing the live lectures.

Introduction to Rates and Survival Analysis

Please ensure you meet the following prerequisites before booking:

Knowledge	Participants should be familiar with the basic Stata commands used to open a dataset, get help on a command, and explore, create and edit variables. Participants should have a knowledge of regression analyses and their implementation in Stata of at least the level achieved in the Introduction to Linear and Logistic Regression Models short course.
Software	Participants will need a computer and internet connection capable of video conferencing whilst running Stata (datasets used in the course are all small). You must have Stata (version 12 or later)* installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).
Recommendation	The Stata practicals will be much easier if you have two screens (one for Stata, one for the instructions). If you do not have a second screen but have access to a printer, some practicals may be easier if you print the practical instructions in advance of the course. We will provide these as a printable pdf file.

Knowledge

Participants should be familiar with the basic Stata commands used to open a dataset, get help on a command, and explore, create and edit variables.

Participants should have a knowledge of regression analyses and their implementation in Stata of at least the level achieved in the Introduction to Linear and Logistic Regression Models short course.

Software

Participants will need a computer and internet connection capable of video conferencing whilst running Stata (datasets used in the course are all small). You must have Stata (version 12 or later)* installed in advance of the course.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

Recommendation

The Stata practicals will be much easier if you have two screens (one for Stata, one for the instructions). If you do not have a second screen but have access to a printer, some practicals may be easier if you print the practical instructions in advance of the course. We will provide these as a printable pdf file.

Introduction to Stata

Please ensure you meet the following prerequisites before booking:

Software	You must have Stata (ideally version 19, but we can accommodate version 14 or later)* installed in advance of the course. Please note that the older versions may have slightly different functionalities. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).
Recommendation	A copy of the course manual will be emailed to you in advance of the course. To facilitate practical sessions we recommend that you either print the course manual yourself, have it open on another device (like a tablet or phone), or split your screen between the manual, your own version of Stata and the Stata the tutor is sharing in Blackboard. If available, a second screen would be ideal for splitting your screen between these different programs.

Software

You must have Stata (ideally version 19, but we can accommodate version 14 or later)* installed in advance of the course. Please note that the older versions may have slightly different functionalities.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

Recommendation

A copy of the course manual will be emailed to you in advance of the course. To facilitate practical sessions we recommend that you either print the course manual yourself, have it open on another device (like a tablet or phone), or split your screen between the manual, your own version of Stata and the Stata the tutor is sharing in Blackboard.

If available, a second screen would be ideal for splitting your screen between these different programs.

Introduction to Statistics

Please ensure you meet the following prerequisites before booking:

Software	Full support will be given for the use of Stata* and R/R studio** in the practical sessions. Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week). *R users - Go to R Installation Instructions for help getting set up.

Software

Full support will be given for the use of Stata* and R/R studio** in the practical sessions.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

**R users - Go to R Installation Instructions for help getting set up.

Introduction to Systematic Reviews and Meta-analysis

Please ensure you meet the following prerequisites before booking:

Knowledge	Participants should have knowledge of statistical methods to the level of our Introduction to Statistics course. A basic appreciation of research designs (to the level of our Introduction to Epidemiology course) would be helpful. Practical sessions will include implementation of meta-analysis methods in computer software, and basic knowledge of R would be helpful for this. Students will have the choice whether to undertake the practicals using (i) R as installed on their computer, or (ii) R using Posit Cloud (Rstudio project).
Software	Participants must either (i) have access to a computer on which R (and Rstudio) is pre-installed, or (ii) a Posit Cloud account (previously called RStudio Cloud). For experienced Stata users, materials can be made available upon request, but participants should be aware that there will be no Stata support offered during the course.

Knowledge

Participants should have knowledge of statistical methods to the level of our Introduction to Statistics course. A basic appreciation of research designs (to the level of our Introduction to Epidemiology course) would be helpful.

Practical sessions will include implementation of meta-analysis methods in computer software, and basic knowledge of R would be helpful for this. Students will have the choice whether to undertake the practicals using (i) R as installed on their computer, or (ii) R using Posit Cloud (Rstudio project).

Software

Participants must either (i) have access to a computer on which R (and Rstudio) is pre-installed, or (ii) a Posit Cloud account (previously called RStudio Cloud). For experienced Stata users, materials can be made available upon request, but participants should be aware that there will be no Stata support offered during the course.

Knowledge Mobilisation in Research

Please ensure you can meet the following prerequisites before booking:

Pre-course work	We ask that you read the blog linked below, which will orient you to the content of the course and help you get the most out of the taught sessions. https://hpruebs.nihr.ac.uk/blog-posts/conversations-about-knowledge-mobilisation-with-public-contributors/ During the course there will be an opportunity to try out creating a knowledge mobilisation plan for your own research. Please come to the course with a research project or topic area in mind. This could be a project you are already working on, an idea you have for a future project or grant application, or just a topic of study which interests you.

Pre-course work

We ask that you read the blog linked below, which will orient you to the content of the course and help you get the most out of the taught sessions.

https://hpruebs.nihr.ac.uk/blog-posts/conversations-about-knowledge-mobilisation-with-public-contributors/

During the course there will be an opportunity to try out creating a knowledge mobilisation plan for your own research. Please come to the course with a research project or topic area in mind. This could be a project you are already working on, an idea you have for a future project or grant application, or just a topic of study which interests you.

Machine Learning with Omics Data

Please ensure you meet the following prerequisites before booking:

Knowledge	You should be very familiar with the topics presented in our Molecular Epidemiology short course. This includes practical knowledge of using R to analyse high-throughput molecular data. It is recommended that you should have either completed the Molecular Epidemiology short course in this programme or have previous experience performing an omic-wide association studies, e.g. GWAS, EWAS, PWAS.
Software	Practical knowledge of using R to analyse high-throughput molecular data is required.
Recommendation	Access to two screens will be useful for practical sessions where one screen can be used to view instructions and the other to carry out instructions and view outputs.

Mendelian Randomization

Please ensure you meet the following prerequisites before booking:

Knowledge	Prior experience of using Mendelian randomization is not required, but participants should have an understanding of aetiological epidemiological principles, and ideally be working on causal population health questions. Those intending to take this course should already understand epidemiological principles and have knowledge and skills in statistical analysis to the level of running, and correctly interpreting results from, multivariable regression analyses. Participants must have experience in running such analyses efficiently in Stata and/or R as all practicals on the course will be offered in both Stata and R and the focus of these practicals will be on Mendelian randomization (not learning how to use the statistical packages). Note: it is not necessary for those participating in the course to be able to use both Stata and R, but you must be able to use one of these. Additionally, we have seen a decreasing number of participants who use Stata over the years and it is becoming commonplace to use R for Mendelian randomization analyses. Therefore, if you use Stata, please note that you will be given the option of using Stata within computational practicals or sit in and learn how to use R through listening to and engaging with discussions in the breakout groups using R.
Software	Participants who would like to use Stata need to have installed Stata version 17* (or later) in advance of the course. Those who would like to use R (latest version) need to have this downloaded onto their computer. The operating system can be either Windows or Mac and participants should consider having a fast internet speed for synchronous/live sessions and for downloading data and scripts. Stata users* - Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. However if you are a student, Stata offer a short term free Student licence (one week). **R users - Go to R Installation Instructions for help getting set up.

Knowledge

Prior experience of using Mendelian randomization is not required, but participants should have an understanding of aetiological epidemiological principles, and ideally be working on causal population health questions.

Those intending to take this course should already understand epidemiological principles and have knowledge and skills in statistical analysis to the level of running, and correctly interpreting results from, multivariable regression analyses.

Participants must have experience in running such analyses efficiently in Stata and/or R as all practicals on the course will be offered in both Stata and R and the focus of these practicals will be on Mendelian randomization (not learning how to use the statistical packages).

Note: it is not necessary for those participating in the course to be able to use both Stata and R, but you must be able to use one of these. Additionally, we have seen a decreasing number of participants who use Stata over the years and it is becoming commonplace to use R for Mendelian randomization analyses. Therefore, if you use Stata, please note that you will be given the option of using Stata within computational practicals or sit in and learn how to use R through listening to and engaging with discussions in the breakout groups using R.

Software

Participants who would like to use Stata need to have installed Stata version 17* (or later) in advance of the course.

Those who would like to use R** (latest version) need to have this downloaded onto their computer.

The operating system can be either Windows or Mac and participants should consider having a fast internet speed for synchronous/live sessions and for downloading data and scripts.

*Stata users - Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata. However if you are a student, Stata offer a short term free Student licence (one week).

**R users - Go to R Installation Instructions for help getting set up.

Molecular Epidemiology

Please ensure you meet the following prerequisites before booking:

Knowledge	A basic knowledge of epidemiology is required. Some understanding of molecular terminology would be advantageous. Some practical knowledge of R would be helpful. Please note that this course attracts a highly multi-disciplinary audience. We do our utmost to accommodate this and ask that if in any doubt, prospective participants enquire prior to booking to check that the course is targeted at the right level for their needs.
Recommendation	Access to two screens will be useful for practical sessions where one screen can be used to view instructions and the other to carry out instructions and view outputs.

Knowledge

A basic knowledge of epidemiology is required. Some understanding of molecular terminology would be advantageous. Some practical knowledge of R would be helpful.

Please note that this course attracts a highly multi-disciplinary audience. We do our utmost to accommodate this and ask that if in any doubt, prospective participants enquire prior to booking to check that the course is targeted at the right level for their needs.

Recommendation

Access to two screens will be useful for practical sessions where one screen can be used to view instructions and the other to carry out instructions and view outputs.

Multiple Imputation for Missing Data

Please ensure you meet the following prerequisites before booking:

Knowledge	Familiarity with R or Stata. Familiarity with standard regression models for continuous and binary outcomes beyond a basic level, and familiarity with causal diagrams.
Software	You must have either R or Stata (version 13 or later) installed in advance of the course. You will be offered the option to do everything in either R or Stata. You will be offered the choice to complete practicals in either R* or Stata. If opting for R: Go to R Installation Instructions for further information. *If opting for Stata: You will need to install Stata (version 13 or later) on your computer prior to attending the course. Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

Knowledge

Familiarity with R or Stata. Familiarity with standard regression models for continuous and binary outcomes beyond a basic level, and familiarity with causal diagrams.

Software

You must have either R or Stata (version 13 or later) installed in advance of the course. You will be offered the option to do everything in either R or Stata.

You will be offered the choice to complete practicals in either R* or Stata**.

*If opting for R: Go to R Installation Instructions for further information.

**If opting for Stata: You will need to install Stata (version 13 or later) on your computer prior to attending the course. Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

Optimising Recruitment to Randomised Controlled Trials

Please ensure you meet the following prerequisites before booking:

Knowledge	It would be advantageous if course attendees have some knowledge and understanding of randomised controlled trials (RCTs). The course does not go into detail about the design/conduct of RCTs, and therefore individuals unfamiliar with this study design may consider first attending the Designing and Conducting Pragmatic Randomised Controlled Trials short course. Experience of having worked on an RCT would be particularly beneficial, although not essential.

Knowledge

It would be advantageous if course attendees have some knowledge and understanding of randomised controlled trials (RCTs). The course does not go into detail about the design/conduct of RCTs, and therefore individuals unfamiliar with this study design may consider first attending the Designing and Conducting Pragmatic Randomised Controlled Trials short course. Experience of having worked on an RCT would be particularly beneficial, although not essential.

Reproducible Health Data Science

Conditions	You should only book onto this course if you are able to commit to attending in full and have time to provide detailed feedback. Attendance is monitored. Pre-course activities must be completed prior to the start of the course to avoid delays and disruption for other participants.
Knowledge	Participants should have experience handling health data, and writing and running scripts that analyse that data. Experience with running linux commands to navigate between file directories and to do file management. Expertise is not required in any specific programming language, however demonstrations will use R, bash and Python. Participants are not expected to have any specific scientific or statistical expertise. The example project for the course will run some basic linear models, but understanding these is not essential.
Software	Participants will carry out essential practical activities on their own computers. Software installation instructions will be provided prior to the course along with a short drop-in session for advice. Computers running Windows 11, Mac OS 13+ or Linux (e.g. Ubuntu 22.04+) operating systems can be supported on this course. You may require elevated privileges to install some basic software on your computer such as VS Code, SSH agent (Windows), Xcode command line tools (Mac), Git for Windows including Git Bash (Windows).
Recommendation	Access to two screens will be useful for practical sessions where one screen can be used to view instructions and the other to carry out instructions and view outputs.

R for Health Data Science

Please ensure you meet the following prerequisites before booking:

Eligibility	This course is available to University of Bristol staff and postgraduate researchers only. Candidates must be able to fully attend the course and provide feedback.
Knowledge	Participants should already be familiar with the basics of R and R Studio, for example, installing and loading packages, importing a dataset, and working with data frames. We recommend attending the Introduction to R short course (or a similar introductory course) before enrolling.
Software	Practical sessions will use Posit Cloud, a free web-based version of RStudio. No installation is needed, but you will need to create a free Posit Cloud account, and we will provide a link and setup instructions before the course. Alternatively, if you have R and RStudio on your own computer, you are welcome to use these if you prefer (a recent version of R is recommended). See R Installation Instructions for further information.
Conditions	Pilot courses are extremely popular and all live sessions must be attended in full. You should only book onto this course if you are able to commit to attending in full and have time to provide detailed feedback. Attendance is monitored. Failure to attend in full, without a valid reason, will result in your access to pilot course materials being rescinded and you will not be permitted to attend any further pilot courses within the same academic year.
Recommendation	We recommend using two screens, or a large screen, so that you can complete the practical work alongside viewing the live sessions. A stable internet connection is required, as all sessions are delivered live online.

Statistical Methods for Mediation Analysis

Please ensure you meet the following prerequisites before booking:

Knowledge	Participants should have knowledge of regression analyses and their implementation in Stata of at least the level achieved in the Introduction to Linear and Logistic Regression Models short course.
Software	You must have Stata* (version 14, 15, 16 ,17, 18 or 19) installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).

Knowledge

Participants should have knowledge of regression analyses and their implementation in Stata of at least the level achieved in the Introduction to Linear and Logistic Regression Models short course.

Software

You must have Stata* (version 14, 15, 16 ,17, 18 or 19) installed in advance of the course.

*Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course.

External participants are responsible for providing their own access to Stata, however if you are a student, Stata offer a short term free Student licence (one week).