Training Calendar

Stata Programming: Introduction and Advanced

Online 4 days (15th June 2020 - 18th June 2020) Stata Advanced, Introductory
Big Data, Econometrics, Macroeconomics, Programming, Statistics

Course Overview

This course, presented in a two part sequence, will teach Stata Programming at an introductory and advanced level.

The first part, is for Stata users, professionals and researchers from all academic disciplines, who would like to use Stata programming techniques to enhance the efficiency and reliability of their research. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. The participants will learn how to use do-file programming techniques effectively, including topics such as local and global macros, r-returns and e-returns, implicit and explicit loops and debugging techniques.

The second part, is for users who have completed the companion course Introduction to Stata Programming and would like to use more advanced features of the Stata and Mata programming languages. The course assumes familiarity with Stata’s command-line interface and the use of do-files and log files to produce reproducible results. The participants will learn how to implement new Stata commands with ado-files and egen functions. Mata programming techniques will illustrate how this language can be used to simplify and accelerate computations.

Introduction to Stata Programming 15th - 16th June

Two days of online instruction for four hours per day.

Two hours of lecture each morning, one hour of lecture each afternoon, followed by a one hour hands-on session.

Day 1

Session 1: Some fundamental concepts

  • • Do and ado files in Stata
  • • Data types: Working with dates and time, time series operators, factor variables
  • • Debugging – the capture command
  • • Protecting your data with preserve and restore
  • Session 2: Programming do-files

  • • transformation of string and numeric variables
  • • recoding discrete and continuous variables
  • • recoding missing variables
  • • generate and egen functions
  • • local and global macros
  • • extended macro functions and list functions
  • • scalars and matrices
  • • temporary variables and tempnames
  • • looping commands: forvalues and foreach
  • • by, statsby, rolling and other prefix commands
  • • transforming data with reshape
  • • combining datasets with append and merge
  • Session 3: Practical session in Stata

    Day 2

    Session 1: Concepts and tools in action

  • • Tabulating and computing statistics across a set of variables and groups
  • • Computing durations and aggregating transactions data
  • • summarizing group characteristics over observations
  • • adding aggregate characteristics to micro observations
  • • Reusing results : return and ereturn commands
  • • Accessing estimation results and margins
  • Session 2: Automation for tables and graphs

  • • Storing results in matrices
  • • Stata’s post and postfile commands
  • • Automating estimation output – the user-written commands estout and tabout, saveresults
  • • Automating graphical output
  • Session 3: Practical session in Stata

    Advanced Stata Programming 17th - 18th June

    Two days of online instruction for four hours per day.

    Two hours of lecture each morning, one hour of lecture each afternoon, followed by a one hour hands-on session.

    Day 1

    Session 1: Introduction to ado-file programming

  • • structure of an ado-file
  • • syntax and return statements
  • • using program options
  • • including a subset of observations
  • • generalizing commands to handle multiple variables
  • • rendering commands byable
  • Session 2: e-class programs and egen functions

  • • writing an e-class program
  • • programs for egen, ml, nl
  • • programs for gmm
  • • Guidelines for ado-file programming style
  • Session 3: Practical session in Stata

    Day 2

    • Session 1: Introduction to Mata

  • • Mata Fundamentals
  • • One-line use of Mata in a do-file
  • • A simple Mata function
  • • Components of a Mata function
  • • Calling Mata functions
  • • Mata’s st_interface functions
  • • Session 2: Mata’s advanced features

  • • Mata-based likelihood function evaluators
  • • Creating arrays of temporary objects with pointers
  • • Structures
  • • Examples of Mata usage
  • Session 3: Practical session in Stata

    Prerequisites

    • Principal text for pre- and post-course reading:
    • Christopher F Baum. 2016. An Introduction to Stata Programming, Second Edition. College Station, TX: Stata Press.

    Terms and 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.
    • Cost includes course materials, lunch and refreshments.
    • Delegates are provided with temporary licences for the software(s) used in the course and will be instructed to download and install the software prior to the start of the course.
    • Payment of course fees required prior to the course start date.
    • Registration closes 5-calendar days prior to the start of the course.
      • 100% fee returned for cancellations made over 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 delegates is restricted. Please register early to guarantee your place.

    •  CommercialAcademicStudent
      Part 1 only (2-day course) (15/06/2020 - 16/06/2020)
      Parts 1 & 2 (4-day course) (15/06/2020 - 18/06/2020)
      Part 2 only (2-day course) (17/06/2020 - 18/06/2020)

    All prices exclude VAT or local taxes where applicable.

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