Stata Winter School Online

Overview

The Stata Winter School consists of a series of one and two-day courses which can be taken individually or as a whole as required. The School is aimed at students, academics and professionals who want to develop and strengthen their data processing, programming, graphics and statistical skills using Stata. All of the courses are taught interactively using a blend of theory, follow-along demonstrations and exercises.

Day 1: Tim Collier (London School of Hygiene & Tropical Medicine)

An Introduction to Stata is one-day introductory course for people interested in learning to using Stata for research. This course requires no prior knowledge of Stata but assumes an interest in research and in learning to use Stata efficiently. This course introduces you to the Stata working environment, introduces the two main ways of working in Stata, and to some of the essential tools for data management. The examples used throughout will be from the field of medical statistics. However, the underlying principles will have application in many areas of research. Throughout the day we will emphasise good practice for data management and visualisation. Participants will be able to take away a set of course notes and data used on the course as well as files created throughout the day. There will be opportunities to ask questions throughout the course.

• Introduction to the Stata working environment
• Two ways of working in Stata: the Graphical User Interface and do-files
• Understanding Stata’s command syntax
• Importing data from Excel
• Getting to know your data
• Generating new variables
• Housekeeping for tidy data
• Saving results in a log file

Day 2, Tim Collier (London School of Hygiene & Tropical Medicine)

Data Management using Stata is a one-day course intended for people who have some prior experience with Stata but who would like to develop their data management skills and be able to work more efficiently. This course covers importing data from Excel, combining datasets, and tools for dealing with numeric variables, string variables and dates. The course also covers some basic programming tools, including loops, to improve efficiency with repetitive tasks. We will focus mainly on building up commands in do-files.

• Importing data from Excel
• Combining datasets – merging and appending
• Commands for creating new variables
• Dealing with string variables
• Working with dates in Stata
• Creating summary data sets
• Working efficiently with loops

Day 3, Tim Collier (London School of Hygiene & Tropical Medicine)

Data Visualisation using Stata is a one-day course intended for people who would like to be able to produce publication-quality graphs using Stata. During the course we will create a number of different graph types using the Graphical User Interface. We will start with a simple example and build in complexity. Many of the options available for creating clear, effective, publication-ready graphs will be demonstrated. We will learn how to save the command syntax in a do-file to enable the graph to be easily reproduced and edited if required. We will also cover graph schemes and exporting graphs in different formats.

• Introduction to Stata graphics and useful resources.
• Creating graphs through the Graphical User Interface.
• Saving graph commands in do-files for efficient reproduction.
• Graph options – making a graph ready for publication.
• Saving graphs for presentations.
• Exporting graphs in different formats.
• Good practice for creating effective graphs.

Day 4, Prof. Sébastien LAURENT, (Aix-Marseille Université)

• Session 1: Panel versus Cross-sectional data. Introduction to the concept of exogeneity. A first simple static panel model: the first difference model.
• Session 2: More advanced static panel models: fixed effects models and Random effects models. Testing the relevance of random effects models in a robust way. Testing for heteroscedasticity and serial correlation in a panel context.

Day 5, Prof. Sébastien LAURENT (Aix-Marseille Université)

• Session 1: Introduction to dynamic panel data models and to the concept of Instrumental Variables.
• Session 2: Estimation of dynamic panel models model: the Arellano–Bond estimator, the Arellano Blundell–Bond estimator.

Q&A Session

Prerequisites

Day 1

No previous experience of Stata is required. The two books below would be useful pre-course reading, though not required

• A Gentle Introduction to Stata, Fifth Edition - Alan C. Acock
• An Introduction to Stata for Health Researchers, Fourth Edition - Morten Frydenberg, Svend Juul

Day 2

Some prior experience of Stata is required e.g. attending Course 1 of the Stata Winter School. The two books below are useful accompaniments to the course, but are not required reading.

• The Workflow of Data Analysis Using Stata - J. Scott Long
• Data Management Using Stata: A Practical Handbook - Michael N. Mitchell

Day 3

Some prior experience of Stata would be useful e.g. attending Course 1 of the Stata Winter School. The book below is a useful accompaniment to the course, but is not required reading.

• A Visual Guide to Stata Graphics, Third Edition - Michael N. Mitchell

Day 4

Basic knowledge of linear regression and time series of econometrics is assumed. An introductory level of STATA helps but is not necessary.

Day 5

Basic knowledge of linear regression and time series of econometrics is assumed. An introductory level of STATA helps but is not necessary.

Terms & Conditions

• Student registrations: Attendees must provide proof of full time student status at the time of booking to qualify for student registration rate (valid student ID card or authorised letter of enrolment).
• Additional discounts are available for multiple registrations.
• Delegates are provided with temporary licences for the principal software package(s) used in the delivery of the course. It is essential that these temporary training licenses are installed on your computers prior to the start of the course.
• Payment of course fees required prior to the course start date.
• Registration closes 1 calendar day prior to the start of the course.
  • 100% fee returned for cancellations made more than 28-calendar days prior to start of the course.
  • 50% fee returned for cancellations made 14-calendar days prior to the start of the course.
  • No fee returned for cancellations made less than 14-calendar days prior to the start of the course.

The number of attendees is restricted. Please register early to guarantee your place.