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StataCorp StataMP 15.1 (Revision 20 Sep 2018)

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Standart StataCorp StataMP 15.1 (Revision 20 Sep 2018) StataCorp StataMP 15.1 (Revision 20 Sep 2018)


StataCorp Stata/MP 15.1 (Revision 20 Sep 2018) | 1.0 Gb

StataCorp LLC. is pleased to announce the availability of Stata 15.1 (Revision 20 Sep 2018), is a complete, integrated statistical software package that provides everything you need for data analysis, data management, and graphics.

[b
Update history:[/b]

Stata 15.0 base - 06 jun 2017
Stata 15.1 base - 06 nov 2017
updated to - 20 sep 2018

update 20 Sep 2018

- Online help and the search index have been brought up to date for Stata Journal 18(3).
- bootstrap, when used with panel-data commands and variables having time-series operators, produced incorrect standard errors. More lagged observations than necessary were excluded from the bootstrap replication samples. Under standard assumptions, the reported standard-error estimates were conservative. Stata's xt estimation commands that allow both time-series operators and the vce(bootstrap) option were also affected. This has been fixed.
- levelsof, when used with strL variables and with only one observation in the dataset, produced an error message. This has been fixed.
- margins has the following fixes:
a. margins, after fitting a model with an offset, when options expression() and at() were both specified, in rare cases computed margins from the expression using only the first observation instead of the entire estimation sample. Specifically, only the first observation was used when the expression included more than a single prediction, the prediction relied on the offset, and each variable included in option at() was set to a constant value. This has been fixed.
b. margins with option nose, option dydx(), and multiple predict() options reported marginal effects using only the first predict() option instead of computing the marginal effect for all specified predictions. This has been fixed.
- mixed with option dfmethod(kroger) or option dfmethod(satterthwaite), when group identifiers were string variables, exited with an uninformative error message. This has been fixed.
- predict after menl now estimates predictions for observations with a missing dependent variable.
- Beginning with the 07 August 2018 update, reshape wide with option string and option j(varname), where varname was a string variable containing spaces, did not correctly identify unique values of varname if the characters before the first space were identical for two or more categories of varname. reshape wide now exits with an error message indicating that string j variables are not allowed to contain spaces.
To use a string variable that contains spaces with reshape wide, you can first create a corresponding numeric variable using encode and then specify the resulting variable in reshape's option j().





About Stata 15. Stata 15 is remarkable for its sheer size. This list some here and make some snappy , The most thorough coverage, of course, is at the Stata 15 features page at the stata.com website.

Here are sixteen of the :

- Extended regression. It fits continuous, binary, ordered responses with (1) endogenous covariates, (2) endogenous (Heckman-style) selection, and (3) endogenous treatment effects. This command does a lot and is easy to use.
- Latent class analysis. Binary outcomes. Ordinal outcomes. Continuous outcomes (latent profile analysis). Even incorporate latent classes in path models.
- Bayesian prefix command. You can now type -bayes:- in front of estimation commands to fit Bayesian regression models for over fifty likelihoods. And multilevel models are among them!
- Dynamic stochastic general equilibrium (DSGE) models. Fit structural macro models based on theory with lots of equations. Graph impulse-response functions afterward.
- Markdown for Stata. You can now combine Markdown text with executable Stata code to produce web containing prose, Stata output, parts of Stata output, and graphs. By parts, we mean you can write a sentence such as "The F statistic is 52.4 and R30;", where the 52.4 is obtained from -e(F)-.
- Nonlinear mixed-effects models. Because some problems are just not linear in the parameters.
- Spatial autoregressive models (SAR). Download shapefiles from the web, merge with your geographic-based data, and fit your SAR models with cross-sectional or panel data.
- Interval-censored parametric survival-time models. For when you only know a time when subjects have not yet failed and another when they have already failed.
- Finite mixture models (FMMs). The new -fmm:- command is a prefix command. You mix one or more regression models using any of 17 existing estimation commands.
- Mixed logit models. Discrete choice models with random coefficients, meaning you can relax the IIA assumption.
- Nonparametric regression. Our implementation uses kernel methods. Bootstrap standard errors. Graph slices after fitting. Predict derivatives or levels.
- Power analysis for cluster-randomized designs (CRDs) and for regression models. You can now add your own power and sample-size methods too.
- Word and PDF documents. It's now just as easy to produce Word and PDF documents as it is to produce Excel worksheets.
- Graph color transparency/opacity. Stata's colors used to be fully opaque, which is to say, not-at-all transparent. Now you can change them so that you can see what's underneath.
- ICD-10-CM/PCS support. These are the codes from NCHS and CMS that are mandated for all medical billing in the U.S. Support means a database system that can even manage codes from different versions in one file!
- Federal Reserve Economic Data (FRED) support. 470,000 U.S. and international economic and financial time series are available to registered users courtesy of the St. Louis Federal Reserve Bank. You should register. It's free and easy. If you do, Stata can browse, search, and assemble datasets for you.

The sixteen features listed above certainly important ones, but there are others worthy of mention:

- Bayesian multilevel models
- Threshold regression
- Panel-data tobit with random coefficients
- Multilevel regression for interval-measured outcomes
- Multilevel tobit regression for censored outcomes
- Panel data cointegration tests
- Tests for multiple breaks in time series
- Multiple-group generalized SEM
- Heteroskedastic linear regression
- Poisson models with Heckman-style sample selection
- Panel-data nonlinear models with random coefficients
- Bayesian panel-data models
- Panel-data interval regression with random coefficients
- SVG export
- Bayesian survival models
- Zero-inflated ordered probit
- Add your own power and sample-size methods
- Bayesian sample-selection models
- Stata in Swedish
- Improvements to the Do-file Editor
- Stream random-number generator
- Improvements for Java plugins
- More parallelization in Stata/MP

About Stata/MP. Stata/MP lets you analyze data in one-half to two-thirds the time compared with Stata/SE on inexpensive dual-core laptops and in one-quarter to one-half the time on quad-core desktops and laptops. Stata/MP runs even faster on multiprocessor servers. Stata/MP supports up to 64 cores/processors.

Speed is often most crucial when performing computationally intense estimation procedures. A few of Stata's estimation procedures, including linear regression, are nearly perfectly parallelized, meaning they run twice as fast on two cores, four times as fast on four cores, eight times as fast on eight cores, and so on. Some estimation commands can be parallelized more than others. Taken at the median, estimation commands run 1.9 times faster on 2 cores, 3.1 times faster on 4 cores, and 4.3 times faster on 8 cores.

Speed can also be important when managing large datasets. Adding new variables is nearly 100 percent parallelized, and sorting is 75 percent parallelized.

Some procedures are not parallelized and some are inherently sequential, meaning they run the same speed in Stata/MP.

About StataCorp LLC. StataCorp LP develops, distributes, and supports statistical software. Its products include Stata, which provides an integrated statistics, graphics, and data-management solution for data analyzers; and Stata/MP, which provides support for multiple-processor computers and multicore computers of various statistics and data-management packages. The company also offers two and three day courses, on-site training courses, short courses, seminars, and Web-based courses for learning Stata. In addition, it publishes a peer-reviewed quarterly journal, as well as books on Stata and statistics. Further, StataCorp LP sells mugs, shirts, caps, polos, mouse pads, USB drives, bookmarks, computer briefcases, natural sandstone coasters, black Stata tote, books, and journals online. The company primarily serves the government, corporate, and educational sectors. StataCorp LP offers its products through its distributors and resellers in the United States and internationally. The company was founded in 1984 and is based in College Station, Texas.

Product: StataCorp Stata/MP
Version: 15.1 (Revision 20 Sep 2018)
Supported Architectures: 32bit / 64bit
Website Home Page : [url=http://www.stata.com]www.stata.com
Language: english
System Requirements: PC
Supported Operating Systems: Windows XP or above
Size: 1.0 Gb
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