Stata Training: Public training courses

Public training courses are intensive, in-depth courses taught by StataCorp at third-party sites around the country. They are open to individuals and groups.

Course	Dates	Location	Cost	Enroll
Handling Missing Data Using Multiple Imputation	April 4–5, 2012	Washington, DC	$1,295	Enroll
Multilevel/Mixed Models Using Stata	February 9–10, 2012 May 1–2, 2012	Washington, DC	$1,295	Enroll
Panel-Data Analysis Using Stata	April 18–19, 2012	Washington, DC	$1,295	Enroll
Programming an Estimation Command in Stata	March 8–9, 2012	Washington, DC	$1,295	Enroll
Survey Data Analysis Using Stata	May 30–31, 2012	Washington, DC	$1,295	Enroll
Time-Series Analysis Using Stata	March 6–7, 2012	Washington, DC	$1,295	Enroll
Using Stata Effectively	February 7–8, 2012 March 6–7, 2012 April 4–5, 2012 April 25–26, 2012 May 9–10, 2012 June 19–20, 2012	Washington, DC New York City, NY San Francisco, CA Washington, DC Boston, MA Chicago, IL	$950	Enroll

We offer a 15% discount for group enrollments of three or more participants. Please contact us at training@stata.com for details.

Handling Missing Data Using Multiple Imputation
This course will interactively cover all aspects of multiple-imputation (MI) analysis, including creation of MI data using the multivariate normal and chained-equations (or fully conditional specification) imputation methods, manipulation of MI data, and analysis of MI data. The course will provide exercises to reinforce the presented material. (detailed description)
Length: 2 days

Multilevel/Mixed Models Using Stata
This course is an introduction to using Stata to fit multilevel/mixed models. The course will be interactive, use real data, offer ample opportunity for specific research questions, and provide exercises to reinforce what you learn. (detailed description)
Length: 2 days

Panel-Data Analysis Using Stata
This course provides an introduction to the theory and practice of panel-data analysis. After introducing the fixed-effects and random-effects approaches to unobserved individual-level heterogeneity, the course covers linear models with exogenous covariates, linear models with endogenous variables, dynamic linear models, and some nonlinear models. An introduction to the generalized method of moments estimation technique is also included. Exercises will supplement the lectures and Stata examples. (detailed description)
Length: 2 days

Programming an Estimation Command in Stata
This course shows how to write an estimation command for Stata. No Stata or Mata programming experience is required. This course will provide an introduction to basic Stata do-file programming, basic and advanced ado-file programming, and an introduction to Mata, the byte-compiled matrix language that is part of Stata. Exercises will supplement the lectures and Stata examples. (detailed description)
Length: 2 days

Survey Data Analysis Using Stata
This course covers how to use Stata for survey data analysis assuming a fixed population. The course covers the sampling methods used to collect survey data and how they affect the estimation of totals, ratios, and regression coefficients as well as the three variance estimators implemented in Stata's survey estimation commands. Each topic will be illustrated with one or more examples using Stata. (detailed description)
Length: 2 days

Time-Series Analysis Using Stata
This course reviews methods for time-series analysis and shows how to perform the analysis using Stata. Exercises will supplement the lectures and Stata examples. (detailed description)
Length: 2 days

Enroll now or contact us if you would like to see a public training session offered in your area.

Computers with Stata installed are provided at all public training sessions. All training courses run from 8:30 AM to 4:30 PM each day. A continental breakfast, lunch, and an afternoon snack will also be provided; the breakfast is available before the course begins. All participants are encouraged to bring a USB flash drive to all public training sessions; this is the safest and simplest way to save your work from the session.