Accessing and using ‘real-world’ study data: A Stata-based introduction for newcomers to longitudina

Organised by

CLOSER

Presenter

Dr Neil Kaye, Dr Dara O'Neill, Dr Deborah Wiltshire

Date

24/02/2021 - 10/03/2021

Venue

Online via UCLeXtend

Contact

Jennie Blows, j.blows@ucl.ac.uk

Description

Are you new to using longitudinal study data, or are you looking to use ‘real-world’ datasets for the first time? Perhaps you are looking to use longitudinal study datasets for your Dissertation but are unsure where to start?

This course will help you to become familiar with the basics of data access, how to clean and prepare datasets, and how to use, report and interpret outputs of analysis. It uses real datasets from longitudinal studies as guided examples, with interactive quizzes and hands-on analysis tasks to help you become confident in using real-world longitudinal datasets.

By the end of this course, you’ll have a clear understanding of the following;

  • How to access and explore longitudinal study data;
  • How to clean and prepare a ‘real-world’ dataset;
  • How to begin answering research questions by using and reporting outputs from data analysis

Prerequisites: This course is aimed at undergraduates or recent post-graduates with some knowledge of Stata and a basic understanding of statistical techniques. Participants will require access to a computer with Stata version 13 or newer installed (including during the live webinar sessions).

Timing and access

The course commences the week beginning 22nd February 2021, and includes three 60-minutes live webinars on consecutive Wednesdays: 24th February, 3rd and 10th March 2021 from 13.00-14.00 GMT. Requires 6-8 hours study, including participation in the webinars.

You can register now via the UCL Extend website for the course

Who is this course for?

The course is designed for undergraduate and master’s students in social sciences or epidemiology/health research who are interested in learning more about how to access, prepare and analyse real-world longitudinal quantitative data. It is designed as a refresher on existing learning to provide guidance on undertaking quantitative data research in practice.

What prior knowledge do I need?

The content of the course assumes some knowledge of basic statistical techniques (descriptive statistics, regression modelling) and requires some previous experience of using Stata (some familiarity with basic commands). It is suitable for undergraduate-level students and would be particularly useful for students with some quantitative experience. There will be some preparatory reading to do before each session.

When does it run?

The course runs across three weeks, commencing from w/c 22nd February 2021, with live interactive webinars on 24th February, 3rd and 10th March 2021 (from 13.00-14.00 GMT).

How do I use the course?

You will need to register and log-in in advance of the sessions to confirm your participation and to access the course materials. Once you have registered you will be instructed on how to create a free UKDS account so that you can access and download the datasets used in the course.

The course is divided into three sessions: 1) Understanding and Accessing Longitudinal Study Data, 2) Preparing a Dataset for Analysis; and 3) Producing and Reporting Descriptive Statistics and Regression Analyses in Stata. In addition to the interactive webinars, course materials will include quizzes to test your knowledge, assignments to practise in your own time and access to web-based resources (reading lists, useful links, FAQs).

Course team

  • Dr Neil Kaye, Research Fellow at CLOSER, UCL Institute of Education
  • Dr Dara O’Neill, Research Fellow at CLOSER, UCL Institute of Education
  • Dr Deborah Wiltshire, Data Access Manager at UK Data Service

Further information

If you have any questions or require further information about this course, please contact CLOSER Digital Communications and Events Manager, Jennie Blows at j.blows@ucl.ac.uk 

Level

Entry (no or almost no prior knowledge)

Cost

Free

Website and registration

Region

International

Keywords

Quantitative Data Handling and Data Analysis, Longitudinal Data Analysis

Related publications and presentations

Quantitative Data Handling and Data Analysis
Longitudinal Data Analysis

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