__What's new in release 12.0 (compared with release 11)__

This file lists the changes corresponding to the creation of Stata
release 12.0:

+---------------------------------------------------------------+
| help file contents years |
|---------------------------------------------------------------|
| whatsnew Stata 15.0 and 15.1 2017 to present |
| whatsnew14to15 Stata 15.0 new release 2017 |
| whatsnew14 Stata 14.0, 14.1, and 14.2 2015 to 2017 |
| whatsnew13to14 Stata 14.0 new release 2015 |
| whatsnew13 Stata 13.0 and 13.1 2013 to 2015 |
| whatsnew12to13 Stata 13.0 new release 2013 |
| whatsnew12 Stata 12.0 and 12.1 2011 to 2013 |
| **this file** Stata 12.0 new release 2011 |
| whatsnew11 Stata 11.0, 11.1, and 11.2 2009 to 2011 |
| whatsnew10to11 Stata 11.0 new release 2009 |
| whatsnew10 Stata 10.0 and 10.1 2007 to 2009 |
| whatsnew9to10 Stata 10.0 new release 2007 |
| whatsnew9 Stata 9.0, 9.1, and 9.2 2005 to 2007 |
| whatsnew8to9 Stata 9.0 new release 2005 |
| whatsnew8 Stata 8.0, 8.1, and 8.2 2003 to 2005 |
| whatsnew7to8 Stata 8.0 new release 2003 |
| whatsnew7 Stata 7.0 2001 to 2002 |
| whatsnew6to7 Stata 7.0 new release 2000 |
| whatsnew6 Stata 6.0 1999 to 2000 |
+---------------------------------------------------------------+

Most recent changes are listed first.

--- **more recent updates** -------------------------------------------------------

See whatsnew12.

--- **Stata 12.0 release 25jul2011** ----------------------------------------------

__Remarks__

We will list all the changes, item by item, but first, here are the
highlights.

__What's new (highlights)__

Here are the highlights. There is more, and do not assume that because
we mention a category, we have mentioned everything new in the category.
Detailed sections follow the highlights.

1. **Automatic memory management**, which means that you no longer have
to **set** **memory** and never again will you be told that there is no
room because you set too little! Stata automatically adjusts its
memory usage up and down according to current requirements.

The memory manager is tunable. We recommend the default
settings. See **[D] memory** if you are interested.

Old do-files can still **set** **memory**. Stata merely responds, "**set**
**memory** ignored".

2. **Structural equation modeling (SEM)**, via the new **sem** command, is
itself the subject of the new *Stata Structural Equation Modeling*
*Reference Manual*. SEM fits multivariate linear models that can
include observed and latent variables. These models include
confirmatory factor analysis, linear models, instrumental
variables, 2SLS, 3SLS, multivariate regression, seemingly
unrelated least squares, recursive systems, simultaneous systems,
path analysis, latent variables, MIMIC, modeling of direct and
indirect effects, and more. All the above can be estimated by
maximum likelihood with or without missing values, GLS, or ADF
(asymptotic distribution free, also known as GMM). Missing
values are handled using FIML. Raw and standardized coefficients
and effects are reported. All models may be fit across groups
and include tests for group invariance. Modification indices and
score tests are provided.

Models may be specified and reported using commands or
interactive path diagrams. See **[SEM] sem**.

3. **MI**, multiple imputation,

a. **Chained equations**, which is to say, fully conditional
specifications for imputing missing values given arbitrary
patterns for continuous, binary, ordinal, cardinal, or count
variables. See **[MI] mi impute chained**.

b. **Four new imputation methods**. You can impute

1) truncated data,
2) interval-censored data,
3) count data, and
4) overdispersed count data.

See **[MI] mi impute truncreg**, **[MI] mi impute intreg**, **[MI] mi**
**impute poisson**, and **[MI] mi impute nbreg**.

c. **Conditional imputation** is now supported by all univariate
imputation methods, which is to say, you can impute values
for variables with restrictions, such as the number of
pregnancies being imputed only for females, even if female
itself is imputed. See *Conditional imputation* in **[MI] mi**
**impute** and new option **conditional()** in the univariate
imputation entries such as **[MI] mi impute regress**.

d. **Imputation by groups**, which is to say, imputations can be
made separately for different groups of the data. See new
option **by()** in **[MI] mi impute**.

e. **Imputation by drawing posterior estimates from bootstrapped**
**samples**. See new option **bootstrap** in the univariate
imputation entries such as **[MI] mi impute regress**.

f. **Panel-data and multilevel models** are now supported by **mi**
**estimate**. Included are **xtcloglog**, **xtgee**, **xtlogit**, **xtmelogit**,
**xtmepoisson**, **xtmixed**, **xtnbreg**, **xtpoisson**, **xtprobit**, **xtrc**, and
**xtreg**. See **[MI] estimation**.

g. **Linear and nonlinear predictions after MI estimation** using
new commands **mi predict** and **mi predictnl**. See **[MI] mi**
**predict**.

h. **Monte Carlo jackknife error estimates** obtained by omitting
one imputation at a time and reapplying the combination
rules. See new option **mcerror** in **[MI] mi estimate**.

4. **Longitudinal/panel data**,

a. **Survey feature support for xtmixed** including multilevel
sampling weights and robust variance estimators. See **[XT]**
**xtmixed**.

b. **Documentation for xtmixed, xtmelogit, and xtmepoisson** **has been**
**modified to adopt the standard "level" terminology** **from the**
**literature on hierarchical models.** See the *Introduction*
section of *Remarks* in both **[XT] xtmixed** and **[XT] xtmelogit**.

c. **xtmixed now uses maximum likelihood (ML) as the default** **method**
**of estimation**. See **[XT] xtmixed**.

5. **Contour plots**. Filled and outlined plots are available. See
**[G-2] graph twoway contour** and **[G-2] graph twoway contourline**.

6. **Contrasts**, which is to say, tests of linear hypotheses involving
factor variables and their interactions from the most recently
fit model, and that model can be virtually any model that Stata
can fit. Tests include ANOVA-style tests of main effects, simple
effects, interactions, and nested effects. Effects can be
decomposed into comparisons with reference categories,
comparisons of adjacent levels, comparisons with the grand mean,
and more. See **[R] contrast** and **[R] margins, contrast**.

7. **Pairwise comparisons** of means, estimated cell means, estimated
marginal means, predictive margins of linear and nonlinear
responses, intercepts, and slopes. In addition to ANOVA-style
comparisons, comparisons can be made of population averages. See
**[R] pwmean**, **[R] pwcompare**, and **[R] margins, pwcompare**.

8. **Graphs of margins, marginal effects, contrasts, and pairwise**
**comparisons**. Margins and effects can be obtained from linear or
nonlinear (for example, probability) responses. See **[R]**
**marginsplot**.

9. **Time series**,

a. **MGARCH**, which is to say, multivariate GARCH, which is to say,
estimation of multivariate generalized autoregressive
conditional heteroskedasticity models of volatility, and this
includes constant, dynamic, and varying conditional
correlations, also known as the CCC, DCC, and VCC models.
Innovations in these models may follow multivariate normal or
Student's t distributions. See **[TS] mgarch**.

b. **UCM**, which is to say, unobserved-components models, also
known as structural time-series models that decompose a
series into trend, seasonal, and cyclical components, and
which were popularized by Harvey (1989). See **[TS] ucm**.

c. **ARFIMA**, which is to say, autoregressive fractionally
integrated moving-average models, useful for long-memory
processes. See **[TS] arfima**.

d. **Filters for extracting business and seasonal cycles**. Four
popular time-series filters are provided: the Baxter-King
and the Christiano-Fitzgerald band-pass filters, and the
Butterworth and the Hodrick-Prescott high-pass filters. See
**[TS] tsfilter**.

10. **Business dates** allow you to define your own calendars so that
they display correctly and lags and leads work as they should.
You could create file **lse.stbcal** that recorded the days the
London Stock Exchange is open (or closed) and then Stata would
understand format **%tblse** just as it understands the usual date
format **%td**. Once you define a calendar, Stata deeply understands
it. You can, for instance, easily convert between **%tblse** and **%td**
values. See **[D] datetime business calendars**.

11. **Improved documentation for date and time variables**. Anyone who
has ever been puzzled by Stata's date and time variables, which
is to say, anyone who uses them, should see **[D] datetime**, **[D]**
**datetime translation**, and **[D] datetime display formats**.

12. **ROC adjusted for covariates**, which is to say, you can model the
ROC curve and obtain coefficients, standard errors, and graphs.
Nonparametric and parametric estimation is supported. See **[R]**
**rocreg** and **[R] rocregplot**.

13. **Survey SDR weights**, which is to say, successive difference
replicate weights, which are supplied with many datasets from the
U.S. Census Bureau. See **[SVY] svy sdr**.

14. **Bootstrap standard errors for survey data** using user-supplied
bootstrap replicate weights. See **[SVY] svy bootstrap**.

15. **Importing and exporting**,

a. **Excel files**. And the new import preview tool lets you see
the data before you import them. See **[D] import excel**.

b. **EBCDIC files, importing**. And you can convert between EBCDIC
and ASCII formats; see **[D] infile (fixed format)** and **[D]**
**filefilter**.

c. **ODBC connection strings**. See **[D] odbc**.

d. **PDF export for graphs and logs** lets you directly create PDFs
from your Stata results. See **[G-2] graph export** and **[R]**
**translate**.

16. **Renaming groups of variables** is now easy using **rename**'s new
syntax that is 100% compatible with its old syntax. You can
change names, swap names, renumber indices within variable names,
and more. See **[D] rename group**.

17. **Stata interface**,

a. **New layout** is wider and fits most screens better.

b. **New Properties window** lets you manage the properties of your
variables including names, labels, value labels, notes,
display formats, and storage types. And you can manage the
properties of your dataset.

c. **Filtering of Review and Variables windows** lets you type text
and see only the matches.

d. **Searching in the Results window** lets you find results.

e. **Expression Builder now accesses parameter estimates,** **returned**
**results, macros, and more**, so you can build expressions for
**nlcom** and **testnl**. It is worth a test drive.

f. **Unified interface for Mac** means no more lost windows; all the
Stata windows are tied together.

g. **Gesture support for Mac** makes changing font sizes and moving
forward and backward easy.

h. **Tabbed graphs for Mac**.

i. **File drag-and-drop for Windows** -- Stata for Mac already had
it -- now Stata for Windows does, too.

18. **Data Editor**,

a. **New tool for managing variables** lets you hide/show variables
(and includes filtering!), sort variables, and reorder
variables via drag and drop. And it includes Stata's new
Properties tool, so you can manage your data more easily from
the Data Editor. Try it. Click on the Variables tool in the
toolbar.

b. **New Clipboard Preview Tool** lets you see the data before you
paste them into Stata and lets you control how the data will
be pasted.

c. **Clipboard preserves variable properties** such as display
formats and types when you copy-and-paste data within Stata.

19. **All-new Viewer**,

a. **Quick access to dialogs, sections, and "also see" references**
via three pulldown menus at the top of the Viewer for quick
navigation inside help files.

b. **Tabbed Viewer** lets you open multiple help files and documents
and switch between them.

20. **Do-file Editor**,

a. **Tabbed for Mac and Unix** -- Stata for Windows already had it
-- now Stata for Mac and Unix do, too.

b. **Syntax highlighting and bookmarks for Mac** -- Stata for
Windows already had it -- now Stata for Mac does, too.

21. **Estimation output improved**,

a. **Baseline odds now shown**, which is to say, the exponentiated
intercept is displayed by **logistic** and by **logit** with option
**or**. In fact, all estimation commands show exponentiated
intercepts when option **eform()** or its equivalent is
specified. For example, **poisson** shows the baseline incidence
rate when option **irr** is specified.

b. **Implied zero coefficients now shown**. When a coefficient is
omitted, it is now shown as being zero and the reason it was
omitted -- collinearity, base, empty -- is shown in the
standard-error column. (The word "omitted" is shown if the
coefficient was omitted because of collinearity.)

c. **You can set displayed precision for all values in** **coefficient**
**tables** using **set** **cformat**, **set** **pformat**, and **set** **sformat**. Or
you may use options **cformat()**, **pformat()**, and **sformat()** now
allowed on all estimation commands. See **[R] set cformat** and
**[R] estimation options**.

d. Estimation commands now respect the width of the Results
window. This feature may be turned off by new display option
**nolstretch**. See **[R] estimation options**.

e. **You can now set whether base levels, empty cells, and omitted**
**are shown** using **set** **showbaselevels**, **set** **showemptycells**, and
**set** **showomitted**. See **[R] set showbaselevels**.

22. **More MP speed ups**, meaning faster execution for those running
Stata/MP.

a. **Improved MP support for factor variables used in estimation**.
Execution is much faster when there are lots of levels.

b. **Faster maximum likelihood execution with large numbers of**
**covariates**. Processors being assigned on the basis of
variables rather than observations when there are 300 or more
covariates results in improved performance.

c. **Improved performance on 16 or more cores** due to better
tuning.

d. **Up to 64 cores now supported**, up from 32.

23. **Installation Qualification** is now provided by a new tool which
you download for free. The tool produces a report for submission
to regulatory agencies such as the FDA to establish that Stata is
installed correctly. Visit
http://www.stata.com/support/installation-qualification/.

__What's new in the GUI and command interface__

1. **Highlights,**
a. **New layout.**
b. **New Properties window.**
c. **Filtering of Review and Variable windows.**
d. **Searching in the Results window.**
e. **Expression Builder can access parameter estimates, ....**
f. **Unified interface for Mac.**
g. **Gesture support for Mac.**
h. **Tabbed Graphs for Mac.**
i. **File drag-and-drop for Windows.**
j. **Data Editor, new tool for managing variables.**
k. **Data Editor, new Clipboard Preview Tool.**
l. **Data Editor, Clipboard preserves variable properties.**
m. **New Viewer, quick access to dialogs, sections, ....**
n. **New Viewer, tabbed.**
o. **Do-file Editor, tabbed for Mac and Unix.**
p. **Do-file Editor, syntax highlighting and bookmarks for Mac.**
See *What's new (highlights)*.

2. **Aero Snap functionality for Viewer in Windows 7.**

3. **Stata for Unix dialog boxes now have full varlist controls.**

__What's new in data management__

1. **Highlights**,
a. **Automatic memory management.** See **[D] memory**.

b. **Excel files, importing and exporting.** See **[D] import excel**.

c. **EBCDIC files, importing.** See **[D] infile (fixed format)** and
**[D] filefilter**.

d. **ODBC connection strings, importing and exporting.** See **[D]**
**odbc**.

e. **PDF files, exporting of graphs and logs.** See **[R] translate**.

f. **Business dates.** See **[D] datetime business calendars**.

g. **Improved documentation for date and time variables.** See **[D]**
**datetime**, **[D] datetime translation**, and **[D] datetime display**
**formats**.

h. **Renaming groups of variables.** See **[D] rename group**.

See *What's new (highlights)*.

2. **New functions**,

a. **Tukey's Studentized range**, cumulative and inverse,
**tukeyprob()** and **invtukeyprob()**.

b. **Dunnett's multiple range**, cumulative and inverse,
**dunnettprob()** and **invdunnettprob()**.

c. **New date conversion functions** **dofb()** and **bofd()** convert
between business dates and standard calendar dates. See **[D]**
**datetime business calendars**.

See **[FN] Functions by category**.

3. **ODBC support for Oracle Solaris.** See **[D] odbc**.

4. **New Stata commands getmata and putmata** make it easy to transfer
your data into Mata, manipulate them, and then transfer them back
to Stata. **getmata** and **putmata** are especially designed for
interactive use. See **[D] putmata**.

5. **New Stata commands import sasxport, export sasxport, and** **import**
**sasxport, describe** replace existing commands **fdause**, **fdasave**, and
**fdadescribe**. **fdause**, **fdasave**, and **fdadescribe** are understood as
synonyms. See **[D] import sasxport**.

6. **xshell** support for Mac. See **[D] shell**.

__What's new in statistics (general)__

1. **Highlights**,
a. **Contrasts**. See **[R] contrast** and **[R] margins, contrast**.

b. **Pairwise comparisons**. See **[R] pwmean**, **[R] pwcompare**, and **[R]**
**margins, pwcompare**.

c. **Graphs of margins, marginal effects, contrasts, ....** See **[R]**
**marginsplot**.

d. **ROC adjusted for covariates.** See **[R] rocreg** and **[R]**
**rocregplot**.

e. **Estimation output improved**:
**--Baseline odds now shown.**
**--Implied zero coefficients now shown.**
**--You can set displayed precision.** See **[R] set cformat** and
**[R] estimation options**.
**--Estimation commands now respect the width of the** **Results**
**window.** See **[R] estimation options**.
**--You can now set whether base levels, empty cells, and**
**omitted are shown.** See **[R] set showbaselevels** and **[R]**
**estimation options**.

See *What's new (highlights)*.

2. **test with coefficient names not using _b[] notation is now**
**allowed**, even when the specified variables no longer exist in the
current dataset. See **[R] test**.

3. **areg now faster.** **areg** is orders of magnitude faster when there
are hundreds of absorption groups, even if you are not running
Stata/MP. See **[R] areg**.

4. **misstable summarize will now create summary variable** recording
the missing-values pattern. See new option **generate()** for
**summarize** in **[R] misstable**.

5. **margins command supports contrasts.** See **[R] margins, contrast**
and **[R] contrast**.

6. **sfrancia uses better algorithm.** **sfrancia** now uses an algorithm
based on the log transformation for approximating the sampling
distribution of the W' statistic for testing normality. The old
algorithm, using the Box-Cox transformation, is available under
version control or via the new **boxcox** option. Based on
simulation, the new algorithm is more powerful for sample sizes
greater than 1,000 and is comparable to the old algorithm for
sample sizes less than 1,000. Also, similarly to **swilk**, **sfrancia**
now allows you to suppress the treatment of ties when option
**noties** is used. See **[R] swilk**.

7. **logistic now allows option noconstant.** See **[R] logistic**.

8. **Probability predictions now available.** **predict** after count-data
models, such as **poisson** and **nbreg**, can now predict the
probability of any count or count range. See **[R] nbreg**
**postestimation**, **[R] poisson postestimation**, **[R] tnbreg**
**postestimation**, **[R] tpoisson postestimation**, **[R] zinb**
**postestimation**, and **[R] zip postestimation**.

9. **Truncated count-data models now available.** New estimation
commands **tpoisson** and **tnbreg** fit models of count-data outcomes
with any form of left truncation, including truncation that
varies observation by observation. These new commands supersede
**ztp** and **ztnb**. See **[R] tpoisson** and **[R] tnbreg**.

10. **cnsreg checks for collinear variables prior to estimation** and has
new option **collinear**, which keeps the collinear variables instead
of omitting them. The old behavior of always keeping collinear
variables is preserved under version control. See **[R] cnsreg**.

11. **ml improved**,

a. **ml** now distinguishes the Hessian matrix produced by
**technique(nr)** from the other techniques that compute a
substitute for the Hessian matrix. This means that **ml** will
compute the real Hessian matrix of second derivatives to
determine convergence when all other convergence tolerances
are satisfied and **technique(bfgs)**, **technique(bhhh)**, or
**technique(dfp)** is in effect.

The old behavior was to use the **nrtolerance()** value with the
H matrix associated with the **technique()** currently in effect
to determine convergence; this behavior is preserved under
version control.

b. **ml** has new option **qtolerance()** that distinguishes itself from
**nrtolerance()** when **technique(bfgs)**, **technique(bhhh)**, or
**technique(dfp)** is specified. Option **qtolerance()** replaces
**nrtolerance()** when **technique(bfgs)**, **technique(bhhh)**, or
**technique(dfp)** is in effect.

See **[R] ml** and **[R] maximize**.

12. **margins has new option estimtolerance() for setting tolerance**
used to determine estimable functions. See **[R] margins**.

13. **Option addplot() now places added graphs above or below.**
Commands that allow option **addplot()** can now place the added
plots above or below the command's plots.

__What's new in statistics (longitudinal/panel data)__

1. **Highlights**,

a. **MI support for panel-data and multilevel models** including
**xtcloglog**, **xtgee**, **xtlogit**, **xtmelogit**, **xtmepoisson**, **xtmixed**,
**xtnbreg**, **xtpoisson**, **xtprobit**, **xtrc**, and **xtreg**. See **[MI]**
**estimation**.

b. **Survey feature support for linear multilevel models**, **xtmixed**,
including multilevel sampling weights and robust variance
estimators. See **[XT] xtmixed**.

c. **Documentation for xtmixed, xtmelogit, and xtmepoisson** **has been**
**modified to adopt the standard "level" terminology** **from the**
**literature on hierarchical models.** For example, what in
previous Stata versions was considered a one-level model is
now called a two-level model with the observations now being
counted as "level one"; see the *Introduction* section of
*Remarks* in both **[XT] xtmixed** and **[XT] xtmelogit** for more
details.

d. **Contrasts** available after most xt commands. See **[R] contrast**
and **[R] margins, contrast**.

e. **Pairwise comparisons** available after most xt estimation
commands. See **[R] pwcompare** and **[R] margins, pwcompare**.

f. **Graphs of margins, marginal effects, contrasts, and** **pairwise**
**comparisons** available after all xt estimation commands. See
**[R] marginsplot**.

g. **xtmixed now uses maximum likelihood (ML) as the default** **method**
**of estimation**, where previously it used restricted maximum
likelihood (REML). REML is still available with the **reml**
option, and previous behavior is preserved under version
control.

h. **Estimation output improved.**
**--Baseline odds now shown.**
**--Implied zero coefficients now shown.**
**--You can set displayed precision.** See **[R] set cformat** and
**[R] estimation options**.
**--Estimation commands now respect the width of the** **Results**
**window.** See **[R] estimation options**.
**--You can now set whether base levels, empty cells, and**
**omitted are shown.** See **[R] set showbaselevels** and **[R]**
**estimation options**.

See *What's new (highlights)*.

2. **Robust and cluster-robust SEs after fixed-effects xtpoisson.** See
**[XT] xtpoisson**.

3. **New residual covariance structures for multilevel models** include
exponential, banded, and Toeplitz. See **[XT] xtmixed**.

4. **Probability predictions now available.** **predict** after
random-effects and population-averaged count-data models, such as
**xtpoisson** and **xtgee**, can now predict the probability of any count
or count range. See **[XT] xtpoisson postestimation**, **[XT] xtgee**
**postestimation**, and **[XT] xtnbreg postestimation**.

5. **Option addplot() now places added graphs above or below.**
Commands that allow option **addplot()** can now place the added
plots above or below the command's plots. Affected is the
command **xtline**; see **[XT] xtline**.

__What's new in statistics (time series)__

1. **Highlights,**

a. **MGARCH.** See **[TS] mgarch**.

b. **UCM.** See **[TS] ucm**.

c. **ARFIMA.** See **[TS] arfima**.

d. **Filters for extracting business and seasonal cycles.** See **[TS]**
**tsfilter**.

e. **Business dates.** See **[D] datetime business calendars**.

f. **Improved documentation for date and time variables.** See **[D]**
**datetime**, **[D] datetime translation**, and **[D] datetime display**
**formats**.

g. **Contrasts** available after many time-series estimation
commands. See **[R] contrast** and **[R] margins, contrast**.

h. **Pairwise comparisons** available after many time-series
estimation commands. See **[R] pwcompare** and **[R] margins,**
**pwcompare**.

i. **Graphs of margins, marginal effects, contrasts, and** **pairwise**
**comparisons** available after most time-series estimation
commands. See **[R] marginsplot**.

j. **Estimation output improved.**
**--Implied zero coefficients now shown.**
**--You can set displayed precision.** See **[R] set cformat** and
**[R] estimation options**.
**--Estimation commands now respect the width of the** **Results**
**window.** See **[R] estimation options**.
**--You can now set whether base levels, empty cells, and**
**omitted are shown.** See **[R] set showbaselevels** and **[R]**
**estimation options**.

See *What's new (highlights)*.

2. **Spectral densities from parametric models** via new postestimation
command **psdensity** lets you estimate using **arfima**, **arima**, and **ucm**
and then obtain the implied spectral density. See **[TS]**
**psdensity**.

3. **dvech renamed mgarch dvech.** The command for fitting the diagonal
VECH model is now named **mgarch dvech**, and innovations may follow
multivariate normal or Student's t distributions. See **[TS]**
**mgarch**.

4. **Loading data from Haver Analytics supported on all 64-bit**
**Windows.** See **[TS] haver**.

5. **Option addplot() now places added graphs above or below.** Graph
commands that allow option **addplot()** can now place the added
plots above or below the command's plots. Affected by this are
the commands **corrgram**, **cumsp**, **pergram**, **varstable**, **vecstable**,
**wntestb**, and **xcorr**.

__What's new in statistics (survey)__

1. **Highlights**,

a. **Contrasts** available after survey estimation. See **[R] contrast**
and **[R] margins, contrast**.

b. **Pairwise comparisons** available after survey estimation. See
**[R] pwcompare** and **[R] pwcompare postestimation**.

c. **Graphs of margins, marginal effects, contrasts, and pairwise**
**comparisons** available after survey estimation. See **[R]**
**marginsplot**.

d. **Survey SDR weights.** See **[SVY] svy sdr**.

e. **Bootstrap standard errors for survey data.** See **[SVY] svy**
**bootstrap**.

f. **Estimation output improved.**
**--Baseline odds now shown.**
**--Implied zero coefficients now shown.**
**--You can set displayed precision.** See **[R] set cformat** and
**[R] estimation options**.
**--Estimation commands now respect the width of the** **Results**
**window.** See **[R] estimation options**.
**--You can now set whether base levels, empty cells, and**
**omitted are shown.** See **[R] set showbaselevels** and **[R]**
**estimation options**.

See *What's new (highlights)*.

2. **Survey estimation may be combined with new SEM** for structural
equation modeling. See **[SVY] svy estimation** and **[SEM] sem**.

3. **Survey goodness-of-fit** available after **logistic**, **logit**, and
**probit** with new command **estat gof**. See **[SVY] estat**.

4. **Survey coefficient of variation (CV)** available with new command
**estat cv**. See **[SVY] estat**.

__What's new in statistics (survival analysis)__

1. **Highlights**,

a. **Contrasts** available after **stcox**, **stcrreg**, and **streg**. See **[R]**
**contrast** and **[R] margins, contrast**.

b. **Pairwise comparisons** available after **stcox**, **stcrreg**, and
**streg**. See **[R] pwcompare** and **[R] margins, pwcompare**.

c. **Graphs of margins, marginal effects, contrasts, and** **pairwise**
**comparisons** available after **stcox**, **stcrreg**, and **streg**. See
**[R] marginsplot**.

d. **Estimation output improved.**
**--Implied zero coefficients now shown.**
**--You can set displayed precision.**
**--Estimation commands now respect the width of the** **Results**
**window.** See **[R] set cformat** and **[R] estimation options**.
**--You can now set whether base levels, empty cells, and**
**omitted are shown.** See **[R] set showbaselevels** and **[R]**
**estimation options**.

See *What's new (highlights)*.

2. **GĂ¶nen and Heller's K concordance coefficient** available after Cox
proportional hazards estimation. K is robust to censoring. See
new option **gheller** for **estat concordance** in **[ST] stcox**
**postestimation**.

3. **Option addplot() now places added graphs above or below.** Graph
commands that allow option **addplot()** can now place the added
plots above or below the command's plots. Affected by this are
the commands **ltable**, **stci**, **stcoxkm**, **stcurve**, **stphplot**, **strate**,
**sts graph**, and **tabodds**.

__What's new in statistics (multivariate)__

1. **Highlights**,

a. **Structural equation modeling (SEM).** See **[SEM] sem**.

b. **Contrasts.** See **[R] contrast** and **[R] margins, contrast**.

c. **Pairwise comparisons.** See **[R] pwcompare** and **[R] margins,**
**pwcompare**.

d. **Graphs of margins, marginal effects, contrasts, and pairwise**
**comparisons.** See **[R] marginsplot**.

See *What's new (highlights)*.

2. **Option addplot() now places added graphs above or below.** Graph
commands that allow option **addplot()** can now place the added
plots above or below the command's plots. Affected by this are
the commands **screeplot** and **cluster** **dendrogram**; see **[MV] screeplot**
and **[MV] cluster dendrogram**.

__What's new in statistics (multiple imputation)__

1. **Highlights**,

a. **Chained equations.** See **[MI] mi impute chained**.

b. **Four new imputation methods.** See **[MI] mi impute truncreg**,
**[MI] mi impute intreg**, **[MI] mi impute poisson**, and **[MI] mi**
**impute nbreg**.

c. **Conditional imputation.** See *Conditional imputation* in **[MI] mi**
**impute** and new option **conditional()** in the univariate
imputation entries such as **[MI] mi impute regress**.

d. **Imputation by groups.** See new option **by()** in **[MI] mi impute**.

e. **Imputation by drawing posterior estimates from bootstrapped**
**samples.** See new option **bootstrap** in the univariate
imputation entries such as **[MI] mi impute regress**.

f. **Panel-data and multilevel models are now supported.** Included
are **xtcloglog**, **xtgee**, **xtlogit**, **xtmelogit**, **xtmepoisson**,
**xtmixed**, **xtnbreg**, **xtpoisson**, **xtprobit**, **xtrc**, and **xtreg**. See
**[MI] mi estimation**.

g. **Linear and nonlinear predictions after MI estimation.** See
**[MI] mi estimate postestimation**.

h. **Monte Carlo jackknife error estimates.** See new option **mcerror**
in **[MI] mi estimate**.

i. **Estimation output improved.**
**--Baseline odds now shown.**
**--Implied zero coefficients now shown.**
**--You can set displayed precision.** See **[R] set cformat** and
**[R] estimation options**.
**--Estimation commands now respect the width of the** **Results**
**window.** See **[R] estimation options**.
**--You can now set whether base levels, empty cells, and**
**omitted are shown.** See **[R] set showbaselevels** and **[R]**
**estimation options**.

See *What's new (highlights)*.

2. **Handling of perfect prediction** during imputation of categorical
data using **logit**, **ologit**, and **mlogit**. See *The issue of perfect*
*prediction during imputation of categorical data* in **[MI] mi**
**impute** and see new option **augment** in **[MI] mi impute logit**, **[MI]**
**mi impute ologit**, and **[MI] mi impute mlogit**.

3. **Faster imputation.** **mi impute** no longer secretly converts to
**flongsep** and back again.

4. **mi estimate now supports total.** See **[MI] estimation**.

5. **misstable summarize will now create summary variables** recording
the missing-values pattern. See new option **generate()** for
**summarize** in **[R] misstable**. Note that **mi** **misstable** does not have
this new option. The new option is useful before data are
imputed.

6. **mi estimate** and **mi estimate using** now use a small-sample
adjustment when computing fractions of missing information and,
subsequently, when computing relative efficiencies when the
specified estimation command provides complete-data degrees of
freedom. Before, these statistics were always computed assuming
a large sample. Fractions of missing information and relative
efficiencies are reported when the **vartable** option is used. The
old behavior is available under version control.

7. **mi impute monotone** retains in the imputation model imputation
variables that do not contain missing values in the imputation
sample. Before, **mi impute monotone** omitted such variables from
the imputation model, assuming independence between the variables
being imputed and the variables being omitted. The old behavior
is available under version control.

__What's new in graphics__

1. **Highlights**,

a. **Graphs of margins, marginal effects, contrasts, ....** See **[R]**
**marginsplot**.

b. **Contour plots.** See **[G-2] graph twoway contour** and **[G-2] graph**
**twoway contourline**.

c. **PDF export for graphs and logs** lets you directly create PDFs
from your Stata graphs. See **[G-2] graph export** and **[R]**
**translate**.

See *What's new (highlights)*.

2. **Time-series operators now supported** by **twoway lfit**, **twoway lfitci**,
**twoway qfit**, and **twoway qfitci**. See **[G-2] graph twoway lfit**,
**[G-2] graph twoway lfitci**, **[G-2] graph twoway qfit**, and **[G-2]**
**graph twoway qfitci**.

3. **Graphs of marginal and covariate-specific ROC curves.** New
command **rocregplot** plots the fitted ROC curve after **rocreg**. See
**[R] rocregplot**.

4. **Option addplot() now places added graphs above or below.** Graph
commands that allow option **addplot()** can now place the added
plots above or below the command's plots.

__What's new in programming__

1. **Stored results r() and e() can be marked hidden or historical**,
which means they do not show when the user types **return** **list** or
**ereturn** **list** unless the user also specifies option **all**. See **[P]**
**return**.

2. **Estimation commands now store in r() as well as e().** **r()** values
are stored at estimation time and after replaying. Stored are

a. **r(level)**, a scalar containing the confidence level for the
CIs.

b. **r(label***#***)**, a macro containing the label displayed with the
*#*th coefficient, such as "(base)", "(omitted)", or "(empty)".

c. **r(table)**, a matrix containing all the data displayed in the
coefficient table. The matrix is the coefficient table,
transposed; each column contains coefficients and associated
statistics. To understand the matrix, do the following:

**. sysuse auto, clear**
** . regress mpg weight displ**
** . matrix list r(table)**

See **[P] ereturn**.

3. **ereturn display offers new options for controlling the look of**
**the** **coefficient table.**

a. Options **noomitted**, **vsquish**, **noemptycells**, **baselevels**, and
**allbaselevels** control row spacing and display of omitted
variables and base and empty cells.

b. Formatting display options **cformat(%***fmt***)**, **pformat(%***fmt***)**, and
**sformat(%***fmt***)** control the formats of numbers in the
coefficient table.

c. **ereturn display** now respects the width of the Results window.
This feature may be turned off by new display option
**nolstretch**.

See **[R] estimation options**.

4. **Matrices can be in tables with equation names only** using new
options **coleqonly** and **roweqonly**. See **[P] matlist**.

5. **matrix accum allows option absorb()** to accumulate deviations from
the mean within groups. See **[P] matrix accum**.

6. **Version control for random-number generators** is now determined
when the seed is set, not when the generator function is used;
see **[P] version**. New **creturn** result **c(version_rng)** records the
version number currently in effect for random-number generators;
see **[P] creturn**.

7. **fvrevar has new option stub()**, which generates stub+index
variables rather than temporary variables. See **[R] fvrevar**.

8. **mprobit now posts base outcome equation to e(b).** See **[R]**
**mprobit**.

9. **Default time for network timeouts was reduced.** **timeout1** has been
reduced from 120 seconds to 30, and **timeout2** has been reduced
from 300 seconds to 180. See **[R] netio**.

__What's new in Mata__

1. **New Stata commands getmata and putmata** make it easy to transfer
your data into Mata, manipulate them, and then transfer them back
to Stata. **getmata** and **putmata** are especially designed for
interactive use. See **[D] putmata**.

2. **New functions** imported from Stata,

a. **Tukey's Studentized range**, cumulative and inverse,
**tukeyprob()** and **invtukeyprob()**.

b. **Dunnett's multiple range**, cumulative and inverse,
**dunnettprob()** and **invdunnettprob()**.

c. **New date conversion functions** **dofb()** and **bofd()** convert
between business dates and standard calendar dates. See **[D]**
**datetime business calendars**.

See **[FN] Functions by category**, **[M-5] normal()**, and **[M-5] date()**.

3. **Support for hidden and historical saved results.** Existing Mata
functions **st_global()**, **st_numscalar()**, and **st_matrix()** now allow
an optional third argument specifying the hidden or historical
status. Three new functions -- **st_global_hcat()**,
**st_numscalar_hcat()**, **st_matrix_hcat()** -- allow you to determine
the saved hidden or historical status. See **[M-5] st_global()**,
**[M-5] st_numscalar()**, and **[M-5] st_matrix()**.

4. **Support for new ml features.** Stata's **ml** now distinguishes the
Hessian matrix produced by **technique(nr)** from the other
techniques that compute a substitute for the Hessian matrix.
This means that **ml** will compute the real Hessian matrix of second
derivatives to determine convergence when all other convergence
tolerances are satisfied and **technique(bfgs)**, **technique(bhhh)**, or
**technique(dfp)** is in effect.

Mata's commands **optimize()** and **moptimize()** have been similarly
changed. See **[M-5] optimize()** and **[M-5] moptimize()**.

__What's more__

We have not listed all the changes, but we have listed the important
ones.

Stata is continually being updated, and those updates are available for
free over the Internet. All you have to do is type

**. update query**

and follow the instructions.

To learn what has been added since this manual was printed, select **Help >**
**What's New?** or type

**. help whatsnew**

We hope that you enjoy Stata 12.

__Reference__

Harvey, A. C. 1989. *Forecasting, Structural Time Series Models and the*
*Kalman Filter*. Cambridge: Cambridge University Press.

-------- **previous updates** -----------------------------------------------------

See whatsnew11.

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