In this presentation, I discuss a variety of ways in which you can interpret
the results obtained from nonlinear models (e.g.,
logit,
probit,
poisson, and
streg) and how these different
ways of interpreting results are related. I pay particular attention
to 1) the difference between average predictions or
marginal effects and predictions or marginal effects for
an individual with average characteristics; 2) the different ways in which
interaction effects can be interpreted; and 3) the difficulties in giving an
causal interpretation to effects in nonlinear models.
Additional information
buis_sug.pdf
This session introduces the use of the
margins command to estimate
the partial effects at the mean and the mean of the partial effects. Both
the Stata syntax and the underlying statistical methods will be discussed.
The presentation will also include some discussion of factor variables.
Additional information
drukker_sug.pdf
Multiple imputation is a method for trying to retrieve power lost by missing
values in a dataset. In this session, I will demonstrate how the suite
of
mi commands introduced in Stata 11 can be used to impute data,
estimate models, and pool results, as well as manage various forms of
multiply imputed datasets.
Additional information
rising_sug.pdf
Università Commerciale L. Bocconi, Milano
The “Wishes and grumbles” session offers participants the
opportunity to interact directly with StataCorp. You can highlight problems
or limitations of the software and suggest improvements or new commands that
possibly could be included in the next version of Stata.
