Stata 12
Feature List | New Features | System Requirements | Further Information
What is Stata?
Stata 12 is your complete system for managing, graphing, and analyzing
data. It is easy to learn through the extensive graphical interface yet
is completely programmable for the most demanding data management and
statistical requirements.
|
| Easy to learn yet fully programmable
for the most demanding data management and statistical requirements
With a point-and-click interface, an intuitive command syntax, and online help,
Stata is easy to use, fast, and accurate (see
certification results and
FDA document compliance for details). All analyses can be reproduced and documented
for publication and review.
With Stata's menus and dialogs, you can easily point and click or drag
and drop your way to all of Stata's statistical, graphical, and data management
features. You can completely reshape your data, create group-level variables
for panel or longitudinal data, graph a receiver operating characteristics
(ROC) curve or impulse-response function (IRF), perform a case-control
analysis, estimate a random-effects count-data model or a Cox proportional
hazards model, or compute marginal effects from a nonlinear estimator.
You can even access the dialog boxes for each command directly from the
online help system. This is a great way to explore all of the capabilities
of Stata.
Stata can also run sets of commands from script .les to automate complex
or repetitive tasks. If you need to perform a sequence of multi-key merges
using multiple .les, produce and compare a set of predicted statistics
from a series of models, or even write your own maximum likelihood estimator,
Stata's complete command-line scripting and programming facilities are
always available. You even have access to all of the tools you need to
create whole new Stata commands – commands that work just like the commands
shipped with Stata.
Whether you enter commands directly or use the menus and dialogs to automatically
collect a sequence of operations, you can create a ledger of all actions
and their results to ensure the reproducibility and integrity of your
analyses.
|
| Statistical breadth with depth
Statistical methods and tools are becoming increasingly interdisciplinary.
Economists, sociologists, and political scientists .nd themselves using
matching to control for unmeasured effects – an area more traditionally
of interest to biostatisticians and epidemiologists. Researchers in health
sciences are analyzing more data from observational studies and must control
for treatments that are not assigned randomly – a concern traditionally
of social scientists. These are just two examples of methods once used
primarily in one or two disciplines that are becoming indispensable tools
for researchers in other disciplines. Researchers need a statistical package
that can address the expanding range of statistical methods and that can
handle their speci.c requirements.
Stata provides a broad range of statistical methods with deep coverage
in areas such as panel or longitudinal data, survival or duration analysis,
univariate and multivariate time series, binary and count data, limited
dependent variables, systems of equations, case-control and case-cohort
analysis, cluster analysis, and many others (see the partial list below).
Whether you are in such social science disciplines as economics, sociology,
or political science; health .elds, such as biostatistics or epidemiology;
business .elds, such as marketing, management, or business analysis; quality
control; statistics; or other research .elds, Stata provides a strong
platform for analyzing your data.
|
Different Stata Packages
Features
New in Stata 12
Stata Documentation
Stata 12 comes in 4 flavours
Whether you're a first-year graduate student or a seasoned research professional, we have a package designed to suit
your needs:
- Stata/MP: The fastest version of Stata (for dual-core and multicore/multiprocessor computers)
- Stata/SE: Stata for large datasets
- Stata/IC: The standard version of Stata
- Small Stata: A smaller, student version of Stata (for educational purchases only)
|
Feature Comparison
| Package |
Max. no of variables |
Max no. of right-hand variables |
Max. no. of observations |
64-bit version available? |
Fastest: designed for parallel processing |
Platforms |
| Stata/MP |
32,767 |
10,998 |
unlimited* |
Yes |
Yes |
Windows, Macintosh(64-bit Intel) or Unix |
| Stata/SE |
32,767 |
10,998 |
unlimited* |
Yes |
No |
Windows, Macintosh or Unix |
| Stata/IC |
2,047 |
798 |
ulimited* |
Yes |
No |
Windows, Macintosh or Unix |
| Small Stata |
99 |
99 |
1,200 |
Yes |
No |
Windows or Macintosh or Unix |
|
* The maximum number of observations is limited only by the amount of available RAM on your system.
What do I obtain?
|
Data management
data transformations, match-merge, ODBC, XML, by-group processing, append files, sort, row–column transposition, labeling,
saving results
Basic statistics
summaries, cross-tabulations, correlations, t tests, equality-of-variance tests, tests of proportions, confidence intervals,
factor variables
Linear models
regression; bootstrap, jackknife, and robust Huber/White/sandwich variance estimates; instrumental variables; three-stage
least squares; constraints; quantile regression; GLS
Multilevel mixed-effects models
continuous, binary, and count outcomes; two-, three-, and multiway random-intercepts and random-coefficients models; crossed
random effects; ML and REML estimation; BLUPs of effects and fitted values; hierarchical models; residual error structures
Binary, count, and limited dependent variables
logistic, probit, tobit; Poisson and negative binomial; conditional, multinomial, nested, ordered, rank-ordered, and
stereotype logistic; multinomial probit; zero-inflated and zero-truncated count models; selection models; marginal effects
Panel data/longitudinal data
random- and fixed-effects with robust standard errors, linear mixed models, random-effects probit, GEE, random- and
fixed-effects Poisson, dynamic panel-data models, and instrumental-variables regression; panel unit-root tests; AR(1)
disturbances
Generalized linear models (GLMs)
ten link functions, user-defined links, seven distributions, ML and IRLS estimation, nine variance estimators, seven residuals
Nonparametric methods
Wilcoxon–Mann–Whitney, Wilcoxon signed ranks and Kruskal–Wallis tests; Spearman and Kendall correlations; Kolmogorov–Smirnov
tests; exact binomial CIs
Exact statistics
exact logistic and Poisson regression, exact case–control statistics, binomial tests, Fisher’s exact test for r × c tables
ANOVA/MANOVA
balanced and unbalanced designs; factorial, nested, and mixed designs; repeated measures; marginal means
Multivariate methods
factor analysis, principal components, discriminant analysis, rotation, multidimensional scaling, Procrustean analysis,
correspondence analysis, biplots, dendrograms, user-extensible analyses
Cluster analysis
hierarchical clustering; kmeans and kmedian nonhierarchical clustering; dendrograms; stopping rules; user-extensible analyses
Resampling and simulation methods
bootstrapping, jackknife and Monte Carlo simulation, permutation tests
Model testing and postestimation support
Wald tests; LR tests; linear and nonlinear combinations, tests, and predictions; marginal means, least-squares means, adjusted
means, average partial and marginal effects; Hausman tests
Graphics
line charts, scatterplots, bar charts, pie charts, hi-lo charts, regression diagnostic graphs, survival plots,
nonparametric smoothers, distribution Q-Q plots
|
Survey methods
sampling weights, multistage designs; stratification, poststratification; deff; means, proportions, ratios, totals; summary
tables; predictive margins; bootstrap, jackknife, and linearization-based variance estimation; regression, instrumental
variables, probit, Cox regression
Survival analysis
Kaplan–Meier and Nelson–Aalen estimators, Cox regression (frailty); parametric models (frailty); competing risks; hazards;
time-varying covariates; left and right censoring, Weibull, exponential, and Gompertz analysis; sample size and power analysis
Tools for epidemiologists
standardization of rates, case–control, cohort, matched case–control, Mantel–Haenszel, pharmacokinetics, ROC analysis, ICD-9-CM
Time series
ARIMA, ARCH/GARCH, VAR, VECM, multivariate GARCH, dynamic factors, state-space models, high-frequency data, correlograms,
periodograms, white-noise tests, unit-root tests, Holt–Winters smoothers, Haver Analytics data, rolling and recursive
estimation
Multiple imputation
five univariate imputation methods, multivariate normal imputation, explore pattern of missingness, manage imputed datasets,
estimate model and pool results, transform parameters, joint tests of parameter estimates
Maximum likelihood
user-specified functions; NR, DFP, BFGS, BHHH; OIM, OPG, robust, bootstrap, and jackknife matrices; Wald tests; survey data;
numeric or analytic derivatives
Other statistical methods
generalized method of moments (GMM), sample size and power, nonlinear regression, stepwise regression, statistical and
mathematical functions
Programming language
adding new commands, command scripting, if, while, command parsing, debugging, menu and dialog-box programming, markup and
control language
Matrix programming—Mata
interactive sessions, large-scale development projects, optimization, matrix inversions, decompositions, eigenvalues and
eigenvectors, LAPACK engine, real and complex numbers, string matrices, interface to Stata datasets and matrices, numerical
derivatives, object-oriented programming
Internet capabilities
ability to install new commands, web updating, web file sharing, latest Stata news
Accessibility
Section 508 compliance, accessibility for persons with disabilities
SSample session
A sample session of Stata for Mac, Unix, or Windows.
User-written commands
User-written commands for meta-analysis, data management, survival, econometrics
GUI
Stata for Windows
Stata for Macintosh
Stata for Unix
Stata for Unix has an all new, more modern GUI.
- find what you need in the menus
- fill in the dialog
- click OK and the dialog will submit the command to Stata
- you may use commands or GUI
|
|
Structural equation modeling (SEM)
- Path diagrams
- Graphical model builder
- Standardized and unstandardized estimates
- Modification indices
- Direct and indirect effects
- Score tests and Wald tests
- Factors scores and other predictions
- Goodness of fit
- Estimation with groups and tests of invariance
- Survey data and clustered data
- Raw or statistical summary data
- FIML estimation with missing at random (MAR) data
- Maximum likelihood, ADF, and GMM estimation
- Flexible extension of multivariate regression, instrumental variables, and simultaneous systems
- Confirmatory factor analysis (CFA), correlated uniqueness models, latent growth models, multiple indicators and
multiple causes (MIMIC), ...
Multiple imputation
- Chained equations
- Conditional imputation
- Impute separately within groups
- Linear and nonlinear predictions
- Measure simulation error
- Panel data and multilevel models
- Impute continuous, ordinal, cardinal, and count variables
Contour plots
Excel® import/export
- Preview tool
- Adjust import based on preview
- More data management: ODBC connections strings, EBCDIC, rename groups of variables, ...
Automatic memory management
- Automatically adjusts to dataset size
- Tunable
- Up to 1 terabyte of memory
Interface
- Manage variables, storage types, notes, and formats without leaving the main interface
- Select variables using filters
- Filter prior commands and search results
- Tabbed Viewer
- Jump to dialogs, related commands, and sections in the online help
- Hide, show, reorder, and filter variables in the Data Editor
- Preview before pasting data
- PDF export of results and graphs
Installation Qualification
- Downloadable
- Report for submission to regulatory agencies
Stata/MP
- More estimators
- Up to 64 cores
|
Contrasts
- Compare reference or adjacent categories
- Compare to grand mean
- Orthogonal polynomials
- Treatment effects
Pairwise comparisons
- Compare means, intercepts, or slopes
- Compare odds ratios
- Bonferroni, Scheffé, Tukey, Dunnett, and other adjustments
Margins plots
- Profile and interaction plots
- Margins, contrasts, and pairwise comparisons
- Potential outcomes
- Comparative graphs
ROC analysis
- Parametric and nonparametric
- Adjustments for covariates
- Case-control regression models
- Bootstrap and model-based SEs
- Area under the curve (AUC) and partial AUC
Multilevel mixed-effects models
- Trend, seasonal, and cyclical components
- Static and dynamic forecasts of components
- Stochastic cycles
ARFIMA
- Long-memory processes
- Fractional integration
- Robust variance estimates
- Static and dynamic forecasts
- Linear constraints
Multivariate GARCH
- Constant conditional correlations (CCC)
- Dynamic conditional correlations (DCC)
- Varying conditional correlations (VCC)
- Multivariate normal and Students’ t errors
- Robust variance estimates
- Level and variance predictions
- Static and dynamic forecasts
Spectral density
- Parametric estimates after ARIMA, ARFIMA, and UCM
- Assess importance of frequencies
Time-series filters
- Trend and cycle decompositions
- Christiano–Fitzgerald band-pass filter
- Baxter–King band-pass filter
- Hodrick–Prescott high-pass filter
- Butterworth high-pass filter
Business calendars
- Trading days
- User definable
- Lags and leads using business days
- Conversions from standard calendar
|
Stata 12 Documentation
With STATA 12 the Docu-Sets are no longer bundled with the product variants. Therefore every full version of STATA
includes
the full Docu-Set as PDF on its CD-ROM. If you prefer printed documents you have to order them seperately. Please ask us.
Following there is a list of available printed STATA Manuals:
- Base Reference Manual (3 volumes)
- Data Management Reference Manual
- Graphics Reference Manual
- Longitudinal/Panel Data Reference Manual
- Mata Reference Manual (2 volumes)
- Multivariate Statistics Reference Manual
- Programming Reference Manual
- Survey Data Reference Manual
- Survival Analysis and Epidemiological Tables Reference Manual
- Time-Series Reference Manual
- User's Guide
- Getting Started Manual
- Quick Reference and Index
|
| |
Windows |
Mac |
Unix |
| Other Requirements |
DVD-ROM drive |
DVD-ROM drive |
Stata for Unix requires a video card that can display thousands of colors or more (16-bit or 24-bit color)
DVD-ROM drive |
| Operating System |
Windows 7*, Windows Vista*, XP Pro/Home*,Server 2008*, Server2003*
* 64-bit and
32-bit Windows varieties for x86, x86-64 |
32-bit Stata for any Mac running Mac OS X 10.5 or greater.
(Universal binary for all
processors including PowerPC and Intel)
64-bit Stata requires Intel-based Mac with a 64-bit processor and Mac OS
X 10.5 or greater |
- Linux
Any 64-bit (x86-64 or compatible) or 32-bit (x86 or compatible) running Linux
- Oracle Solaris
Any 64-bit SPARC or compatible running Solaris 9 or higher
64-bit x86-64 Solaris
version also available
|
| Minimum CPU |
|
|
| Min. RAM |
512 MB |
512 MB |
512 MB |
| Disk Space |
500 MB |
500 MB |
500 MB |
|
German
My Account
Product Description
