You should be very familiar with the topics presented in our Epigenetic Epidemiology short course. This includes, in particular, practical knowledge of using R to analyse microarray data.

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.

Practical sessions will be conducted in R and so participants should have a recent version R installed prior to the start of the course. Go to R Installation Instructions for help getting set up.

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 standard regression methods for continuous and binary outcomes beyond a basic level.

You must have Stata (version 13 or later)* and R** (version 4.0.3 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.

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

Participants should be familiar with using Stata statistical software and implementing survival analyses within Stata. Participants should also be familiar with the basics of survival analysis, to at least the level attained from the short course on Introduction to Rates and Survival Analysis.

You must have Stata (version 11 or later, though we recommend more recent versions)* 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.

Applicants must have knowledge and experience of a variety of linear and logistic regression models and their implementation in Stata, to beyond the level achieved in the Introduction to Linear and Logistic Regression Models course. Familiarity with survival analysis is recommended.

 You must have Stata* (version 14, 15 or 16) 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.

You must have at least basic experience using R for statistical analysis. Experience with R is essential (to the level of the Introduction to R short course) but we will review the necessary aspects of R on the first day.

You must have experience with decision trees and Markov models (value of information desirable but not necessary). Knowledge of cost-effectiveness analysis, specifically on decision trees and Markov models, will be assumed (to the level of the Introduction to Economic Evaluation short course).

You must have R (version 4.0.0 or higher) and RStudio (version 1.2.5 or higher) installed in advance of the course. Go to R Installation Instructions for help getting set up.

A basic knowledge of epidemiology is required and some understanding of molecular genetics 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.

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

Ability to download and install R software (for statistical computing and graphics) to the laptop/desktop prior to starting the course.

It is assumed that participants will have attended the Introduction to Stata course (or be familiar with the contents of this course), AND are able to: open and save datasets; generate and rename variables; label variables and values; restrict commands to a subset of the data using the if, in and by qualifiers; generate a Stata date from a string; change the working directory; and use commands display, list, summarize and tabulate.

Participants should have a working knowledge of basic statistics such as linear regression. However, the course is focused on data management and programming skills rather than statistical content.

You must have Stata (version 15 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.

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.

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.

This course will use RStudio 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).

Participants may find it helpful to have 2 screens. However, this is not a requirement.

No previous experience or knowledge of economics is required. As Microsoft Excel will be used for practical sessions, some experience of using Excel would be helpful.

Course attendees will need access to a recent version of Excel to complete some of the practical sessions.

This course is intended for clinicians, researchers, public health specialists and other health care professionals who have only a basic understanding of epidemiology. Prior knowledge of basic medical statistics so that you understand findings published in peer-reviewed medical journals is important.

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.

 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.

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.

 You must have R (version 4.0.3 or higher) and RStudio (version 1.3.1093 or higher) 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.

You must have RStudio installed on your computer in advance of the course. Go to R Installation Instructions for help getting set up.

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.

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, we suggest that you print the practical instructions in advance of the course. We will provide these as a printable pdf file.

Please will students ensure they have access to statistics software before the start of the course. Full support will be given for the use of Stata* in the practical sessions. Students are welcome to use a different package (e.g. R, SAS, SPSS) if they are confident in its use, but we cannot guarantee we will be able to help if difficulties are encountered.

*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. 

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 session will include implementation of meta-analysis methods in computer software, and either basic knowledge of Stata or familiarity with R would be helpful for this. Students without experience in either will undertake practicals using Stata, and they must have this installed before the start of the course.

Participants must either (i) have access to a computer on which Stata* is pre-installed (version 15 or later) OR (ii) be a regular R user.

*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.

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. 

They 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.

Participants who would like to use Stata need to have installed Stata version 16* (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.

*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.

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

Previous experience of conducting (or training in) qualitative analysis using an interpretive method such as grounded theory, thematic analysis, narrative analysis, or framework analysis.

Familiarity with either Stata or R. 

Familiarity with standard regression methods for continuous and binary outcomes beyond a basic level, and familiarity with causal diagrams.

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

R can be downloaded for free here. Go to R Installation Instructions for help getting set up.

*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.

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.

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.

You must have Stata* (version 14, 15, 16 or 17) 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.

Candidates must have completed a piece of work and be ready to write it up.

This course is only suitable for researchers who have already completed or are well underway with their qualitative data collection and analysis. If you are not yet at that stage please consider booking onto a later course.

In advance of the course please identify one or two published articles that you think are good examples of the kinds of qualitative writing that you aspire to.