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st: Stata 13.1
"William Gould, StataCorp LP" <email@example.com>
st: Stata 13.1
Wed, 30 Oct 2013 12:53:53 -0500
We just released Stata 13.1. It's a free update. Type
. update query
and follow the instructions.
Stata 13.1 has new features in three areas,
1. Added features to -power- for handling ANOVA models and
for adding your own statistics.
2. More models for handling censored continuous outcomes.
3. Added univariate time-series commands.
1. Added features in -power-
First, Stata's -power- command, Stata's command for performing
power and sample size analysis, now handles ANOVA models: one-way,
two-way, and repeated-measures models.
Specify any two of (1) sample size, (2) power, or (3) effect size
and you can calculate the third, and you can calculate over ranges
of the variables to produce tables and graphs.
For more about this new feature, see the Stata News:
Second, the other new feature is the one Yulia Marchenko has been
talking about at the recent User Meetings and Stata Conference:
the ability to add you own tests and statistics to -power-. Write
one program to calculate the power, sample size, or effect size,
and then -power- will produce all the fancy output, tables, and
See the example at the Stata News:
2. Censored continuous outcomes
With censored outcomes, the exact values for some subjects are not
observed; one knows only that the value is in a certain range, or
bottom coded, or top coded. Incomes are known up to $100,000 and
top coded after that.
Stata 13 already had commands for dealing with censored outcomes.
These included -tobit-, -intreg-, -ivtobit-, and more.
What's new in Stata 13.1 is all the things you can do, models you
can fit, and data you can use use with censored outcomes:
1. Panel data and random coefficients. Stata 13 had
-xtintreg-, which allowed for random effects, meaning
random intercepts with censored outcomes. Now you can
handle models with random coefficients, too. And you now
have random intercepts and random coefficients at multiple
levels of the data.
2. Selection models. Stata 13 had selection models. Now it
has selection models combined with censored outcomes.
3. Average Treatment Effects (ATEs). We added
treatment-effects estimators in Stata 13; Stata 13.1
provides treatment-effects estimation with censored
4. Endogenous covariates. Stata obviously had lots of
commands that deal with endogenous covariates. As far as
endogenous covariates and censored outcomes, Stata 13 had
-ivtobit-. New features allow for interval measured data.
5. Multivariate models. Stata 13 had -mvreg-, -sureg-, and
-reg3-. Now we have all of those features for censored
outcomes. Some or all of the outcome variables can be
6. Endogenous switching models. You have one process
describing one regime, another process describing another
regime, and perhaps a third process describing a third
regime; and you have a process that describes regime
assignment. All the processes are potentially correlated.
In Stata 13 you could fit these models. In Stata 13.1 you
can fit them with censored outcomes.
Here's the big news: all these new features can be combined. You
can even fit a tobit model with random effects, random
coefficients, sample selection, and endogenous covariates.
All of the above is available due to the new features we have added
to -gsem-. The manual has been updated, too. Also see the examples
presented in the Stata News at
3. Added univariate time-series commands
Two new commands and an extension to two others calculate,
1. IRFs for ARIMA and ARFIMA models.
IRF stands for Impulse-Response Function.
(Extension to -irf-).
2. Parametric autocorrelation graphs after fitting ARIMA and
(New command -estat ac-.)
3. Stability checks after fitting ARIMA models.
(New command -estat aroots-.)
4. Parametric spectral densities after fitting seasonal ARIMA
(Extension to psdensity)
See in the Stata news
Oh, by the way, we've added three more noncentral chi-squared functions
nchi2tail() reverse cumulative
invnchi2tail() inverse of reverse cumulative
It's free, so what's not to like?
-- Words by Bill Gould and Vince Wiggins.
Work by the Stata Development Team.
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