STATA PROGRAMMING & MANAGING LARGE DATASETS


Timberlake Consultants

Start Date:

End Date:

Application Deadline:

Type

Professional training

Funding Options

Students are able to apply for a 50% discount off the listed course fees - see website for details

Location

-

London

United Kingdom

Start Date:

End Date:

Location

United Kingdom

London

Type

Professional training

Application Deadline:


OVERVIEW

The course focuses on practical programming needs arising when dealing with large datasets, multiple data sources and the programming tools which may help in routinising complex tasks and operating pieces of your work automatically.

It is specifically designed for large datasets analysis, automatising repetitive tasks efficiently. You will be able to make your Stata programs execute more efficiently and time will be devoted to your specific programming needs during the course with hands-on sessions with exercises and automatisation of your own codes.

 

COURSE AGENDA

DAY 1 – MANAGING DATA EFFICIENTLY WITH PROGRAMMING ELEMENTS

  • Session 1: Stata Overview, Managing Working sessions, Data management, extended functions for generating new variables
  • Session 2: Scalars and Matrices, Manipulating stored results and creating output tables
  • Session 3: Programming basics, Macros
  • Session 4: Practical session #1

DAY 2 – INTRODUCTION TO STATA PROGRAMMING

  • Session 1: Extended macro functions, Looping and Conditional statements
  • Session 2: Building Do-files with program elements, Temporary files, Preserving data and recovering data
  • Session 3: Passing Arguments to Do files, Program in do-files
  • Session 4: Practical session #2

DAY 3 – ADVANCED STATA PROGRAMMING

  • Session 1: Writing own programs and creating new commands
  • Session 2: Use of arguments and syntax, Generic Ado files, Debugging
  • Session 3: Automatising output: postfile and file
  • Session 4: Practical session #2

DAY 4 – VISUALISATION TOOLS

  • Session 1: Customising graph elements, Layering and combining multiple graphs
  • Session 2: Special graphs with programming elements
  • Session 3: Visualising spatial data with geographical maps
  • Session 4: Practical session #3