The first day of this MEAFA workshop provides an overall introduction to Stata 11
and demonstrates how to work efficiently with reproducible and tractable
routines. This information is helpful to those who are not familiar with
Stata and those who want become more efficient in their work. The next two days engage
with the theory and application of multilevel/mixed models. The course will
be interactive, use real data, and offer ample opportunity for specific
research questions and for working exercises to enforce what is learned.
Detailed notes will be provided outlining all theory and applications.
Day 1 (February 8):
The content on this day assumes no previous knowledge of Stata. You will be introduced to the
environment of Stata 11 and ways to customize Stata. You will learn basic
data-management techniques, how to use logs and work with reproducible and
tractable do-files, how to run basic statistical and estimation commands,
and how to produce tables and make graphs.
Presenter: Demetris Christodoulou, MEAFA General Convenor
Days 2-3 (February 09–10): Multilevel/Mixed Models Using Stata
The course on mixed models assumes basic knowledge of Stata and of standard
linear regression. The first part will look at the classic random-intercept
linear model. Several approaches will be discussed for fitting this model,
along with the associated benefits and assumptions of each approach. The
second part will focus on random coefficients and the various covariance
structures that can be imposed with multiple random-effects terms. The theme
of the third part can best be described as tricks of the trade, covering
various methods for fitting more complex models, including crossed-effects
models, growth curve models, and models with complex and grouped constraints
on covariance structures. The fourth part will consist of predictions, model
diagnostics, and other postestimation tasks. During the first four parts,
the discussion will be confined to linear mixed models for continuous
responses. The fifth part will focus on models for other types of responses,
in particular, binary and count responses. During this final part of the course,
you will learn that most of what is discussed for linear mixed models can be
applied equally to mixed models with noncontinuous responses.
Presenter: Roberto G. Gutierrez, StataCorp Director of Statistics
