Join us in Seattle or Washington, DC for a public training course in a
classroom setting. Our expert instuctors will teach you to use Stata or
to use one of Stata's advanced statistical procedures. Follow the
discussion in your printed copy of the course notes, and work examples
using Stata on the classroom computers.
Classroom training courses run from 8:30 a.m. to 4:30 p.m. on two
consecutive days. A continental breakfast, lunch, and an afternoon
snack will also be provided.
Web-based training offers the same great content as our classroom
training. And just like our classroom training, web-based training is
designed to be interactive. Watch and listen from your computer as the
instructor teaches; follow along in your printed notes; ask the instructor
questions; and work examples using Stata. The differences are that you
attend web-based training courses in the comfort of your own home or office
and that courses are divided into three to four-hour sessions that take place over
consecutive days.
See how our web-based
training courses work, watch a video demonstration, find technical
requirements, and read our
frequently asked questions.
Learn more »
Introduction to Bayesian Analysis Using Stata
Learn about Bayesian analysis and how to perform it in Stata. The course
will cover fundamental Bayesian concepts and contrast them with classical
frequentist concepts. You will learn about Bayesian statistics, including how
to construct and estimate posterior distributions, select priors, and perform
Bayesian inference. You will become familiar with Bayesian computation using
Markov chain Monte Carlo (MCMC) methods and with how to investigate
convergence and efficiency of MCMC. You will learn how to compute various
posterior summaries, compare Bayesian models, and perform Bayesian hypothesis
testing. You will also learn how to fit Bayesian regression models to
different types of outcomes. By the end of the course, you should be
comfortable performing basic Bayesian analysis in Stata.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Estimating Average Treatment Effects Using Stata
Learn how and when to use Stata’s treatment-effects estimators
to analyze treatment effects in observational data. Use regression
adjustment, inverse probability weights, doubly robust methods,
propensity-score matching, and covariate matching to estimate
average treatment effects (ATEs) and ATEs on the treated. We will
cover the conceptual and theoretical underpinnings of treatment
effects as well as many examples using Stata.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Handling Missing Data Using Multiple Imputation
Learn the fundamentals of multiple imputation for regaining power lost by
missing data. The course covers all aspects of using multiple-imputation
(MI) analysis interactively. Topics include creation of MI data using the
multivariate-normal and chained-equations (aka fully conditional
specification) imputation methods, manipulation of MI data, and analysis of
MI data. Exercises supplement the lessons and Stata examples.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Multilevel/Mixed Models Using Stata
Measure and account for clustering and grouping at multiple levels. Whether
linear or nonlinear, multilevel modeling allows for random intercepts and
slopes at multiple levels, reducing the problems of too-much or too-little
data aggregation. The course is interactive, uses real data, offers
ample opportunity for specific research questions, and provides exercises to
reinforce what you learn.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Panel-Data Analysis Using Stata
Learn both the theory and the 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 nonlinear models. Exercises supplement the lessons and Stata
examples.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Programming Estimation Commands in Stata
Learn everything you need to write your own estimation commands in Stata
including linear estimators, nonlinear estimators, estimators based on
maximum likelihood, and estimators based on the generalized method of
moments (GMM).
Learn how to make your command behave just like an official Stata
command.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Regression Modeling Using Stata
Regression modeling is a fundamental tool for researchers who want to
establish causal quantitative relationships from observational data. Learn
the theoretical concepts necessary to understand regression models and how
to implement them using Stata. With the assistance of the instructor, you
will reinforce those concepts with exercises and examples.
(detailed description)
Length: 1 full day (classroom) or 2 half days (web based)
Structural Equation Modeling Using Stata
Learn how to illustrate, specify, and estimate structural equation models in
Stata, using both Stata's SEM builder and the sem command. The course
introduces several types of models, including path analysis, confirmatory
factor analysis, full structural equation models, and latent growth curves.
Exercises supplement the lessons and Stata examples.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Survey Data Analysis Using Stata
Set up and analyze data from complex survey designs. The course covers the
sampling methods used to collect survey data and how they affect the
estimation of totals, ratios, and regression coefficients. The course also
covers Stata's support for many survey variance estimators, including
linearization, balanced and repeated replications (BRR), and jackknife.
Exercises supplement the lessons and Stata examples.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Time-Series Analysis Using Stata
Learn how to efficiently use Stata for time-series analysis. Topics include
data management, estimation of univariate and multivariate stationary and
nonstationary time series, model selection, hypothesis testing, and
interpretation. Exercises supplement the lessons and Stata examples.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
Using Stata Effectively: Data Management, Analysis, and Graphics Fundamentals
Aimed at both new Stata users and those who wish to learn
techniques for efficient day-to-day use of Stata, this course enables
you to use Stata in a reproducible manner, making collaborative changes and
follow-up analyses much simpler.
Exercises will supplement the lectures and Stata examples.
(detailed description)
Length: 2 full days (classroom) or 4 half days (web based)
