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Stata is a complete, integrated statistical software package that provides everything you need for data analysis, data management, and graphics.

 

Fast, accurate, and easy to use

With both a point-and-click interface and a powerful, intuitive command syntax, Stata is fast, accurate, and easy to use. All analyses can be reproduced and documented for publication and review. Version control ensures statistical programs will continue to produce the same results no matter when you wrote them. 

 

Broad suite of statistical features

Stata puts hundreds of statistical tools at your fingertips: 

 

Linear models

regression  •  censored outcomes  •  endogenous regressors  •  bootstrap, jackknife, and robust and cluster–robust variance  •  instrumental variables  •  three-stage least squares  •  constraints  •  quantile regression  •  GLS

 

Longitudinal data/panel 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  •  instrumental variables  •  panel unit-root tests 

 

Multilevel mixed-effects models

continuous, binary, count, and survival outcomes  •  two-, three-, and higher-level models  •  generalized linear models  •  random-intercepts  •  random-slopes  •  crossed random effects  •  BLUPs of effects and fitted values  •  hierarchical models  •  residual error structures  •  DDF adjustments  •  support for survey data  •  

 

Binary, count, and limited outcomes

logistic, probit, tobit  •  Poisson and negative binomial  •  conditional, multinomial, nested, ordered, rank-ordered, and stereotype logistic  •  multinomial probit  •  zero-inflated and left-truncated count models  •  selection models  •  marginal effects  • 

 

Generalized linear models (GLMs)

ten link functions  •  user-defined links  •  seven distributions  •  ML and IRLS estimation  •  nine variance estimators  •  seven residuals  •  

 

ANOVA/MANOVA

balanced and unbalanced designs  •  factorial, nested, and mixed designs  •  repeated measures  •  marginal means  •  contrasts  

 

Exact statistics

exact logistic and Poisson regression  •  exact case–control statistics  •  binomial tests  •  Fisher’s exact test for r × c tables 

 

Tests, predictions, and effects

Wald tests  •  LR tests  •  linear and nonlinear combinations  •  predictions and generalized predictions  •  marginal means  •  least-squares means  •  adjusted means  •  marginal and partial effects  •  forecast models  •  Hausman tests  •  

 

Contrasts, pairwise comparisons, and margins

compare means, intercepts, or slopes  •  compare to reference category, adjacent category, grand mean, etc.  •  orthogonal polynomials  •  multiple-comparison adjustments  •  graph estimated means and contrasts  •  interaction plots  •  

 

GMM and nonlinear regression

generalized method of moments (GMM)  •  nonlinear regression 

 

Simple maximum likelihood

specify likelihood using simple expressions  •  no programming required  •  survey data  •  standard, robust, bootstrap, and jackknife SEs  •  matrix estimators  

 

Programmable maximum likelihood

user-specified functions  •  NR, DFP, BFGS, BHHH  •  OIM, OPG, robust, bootstrap, and jackknife SEs  •  Wald tests  •  survey data  •  numeric or analytic derivatives  

 

Resampling and simulation methods

bootstrap  •  jackknife  •  Monte Carlo simulation  •  permutation tests

Time series

ARIMA  •  ARFIMA  •  ARCH/GARCH  •  VAR  •  VECM  •  multivariate GARCH  •  unobserved components model  •  dynamic factors  •  state-space models  •  Markov-switching models  •  business calendars  •  correlograms  •  periodograms  •  forecasts  •  impulse-response functions  •  unit-root tests  •  filters and smoothers  •  rolling and recursive estimation 

 

Survival analysis

Kaplan–Meier and Nelson–Aalen estimators,  •  Cox regression (frailty)  •  parametric models (frailty, random effects)  •  competing risks  •  hazards  •  time-varying covariates  •  left- and right-censoring, Weibull, exponential, and Gompertz models 

 

Bayesian analysis

thousands of built-in models  •  univariate and multivariate models  •  linear and nonlinear models  •  continuous, binary, ordinal, and count outcomes  •  continuous univariate, multivariate, and discrete priors  •  add your own models  •  adaptive Metropolis–Hastings sampling  •  Gibbs sampling  •  convergence diagnostics  •  posterior summaries  •  hypothesis testing  •  model comparison  •  

 

Power and sample size

power  •  sample size  •  effect size  •  minimum detectable effect  •  means  •  proportions  •  variances  •  correlations  •  ANOVA  •  case–control studies  •  cohort studies  •  contingency tables  •  survival analysis  •  balanced or unbalanced designs  •  results in tables or graphs  •  

 

Treatment effects

inverse probability weight (IPW)  •  doubly robust methods  •  propensity score matching  •  regression adjustment  •  covariate matching  •  multilevel treatments  •  endogenous treatments  •  average treatment effects (ATEs)  •  ATEs on the treated (ATETs)  •  potential-outcome means (POMs)  •  continuous, binary, count, fractional, and survival outcomes  •  

 

SEM (structural equation modeling)

graphical path diagram builder  •  standardized and unstandardized estimates  •  modification indices  •  direct and indirect effects  •  continuous, binary, count, ordinal, and survival outcomes  •  multilevel models  •  random slopes and intercepts  •  factors scores, empirical Bayes, and other predictions  •  groups and tests of invariance  •  goodness of fit  •  handles MAR data by FIML  •  correlated data  •  survey data

 

Multiple imputation

nine univariate imputation methods  •  multivariate normal imputation  •  chained equations  •  explore pattern of missingness  •  manage imputed datasets  •  fit model and pool results  •  transform parameters  •  joint tests of parameter estimates  •  predictions

 

Survey methods

multistage designs  •  bootstrap, BRR, jackknife, linearized, and SDR variance estimation  •  poststratification  •  DEFF  •  predictive margins  •  means, proportions, ratios, totals  •  summary tables  •  regression, instrumental variables, probit, Cox regression  

 

Cluster analysis

hierarchical clustering  •  kmeans and kmedian nonhierarchical clustering  •  dendrograms  •  stopping rules  •  user-extensible analyses  

 

IRT (item response theory)

binary (1PL, 2PL, 3PL), ordinal, and categorical response models  •  item characteristic curves  •  test characteristic curves  •  item information functions  •  test information functions

 

Multivariate methods

factor analysis  •  principal components  •  discriminant analysis  •  rotation  •  multidimensional scaling  •  Procrustean analysis  •  correspondence analysis  •  biplots  •  dendrograms  •  user-extensible analyses  

 

Nonparametric methods

Wilcoxon–Mann–Whitney, Wilcoxon signed ranks, and Kruskal–Wallis tests  •  Spearman and Kendall correlations  •  Kolmogorov–Smirnov tests  •  exact binomial CIs  •  survival data  •  ROC analysis  •  smoothing  •  bootstrapping  •  

 

Epidemiology

standardization of rates  •  case–control  •  cohort  •  matched case–control  •  Mantel–Haenszel  •  pharmacokinetics  •  ROC analysis  •  ICD-10

Data management

data transformations  •  match-merge  •  import/export data  •  ODBC  •  SQL  •  XML  •  by-group processing  •  append files  •  sort  •  row–column transposition  •  labeling  •  saving results  

 

Graphics

line charts  •  scatterplots  •  bar charts  •  pie charts  •  hi–lo charts  •  contour plots  •  GUI Editor  •  regression diagnostic graphs  •  survival plots  •  nonparametric smoothers  •  distribution Q–Q plots  

 

Graphical user interface

menus and dialogs for all features  •  Data Editor  •  Variables Manager  •  Graph Editor  •  Project Manager  •  Do-file Editor  •  Clipboard Preview Tool  •  multiple preference sets 

 

Documentation 

23 pdf manuals  •  12,000+ pages  •  seamless navigation  •  thousands of worked examples  •  quick starts  •  methods and formulas  •  references 

 

Basic statistics

summaries  •  cross-tabulations  •  correlations  •  zand t tests  •  equality-of-variance tests  •  tests of proportions  •  confidence intervals  •  factor variables 

 

Other statistical methods

kappa measure of interrater agreement  •  Cronbach's alpha  •  stepwise regression  •  tests of normality  

 

Functions

statistical  •  random-number  •  mathematical  •  string  •  date and time 

 

Internet capabilities

ability to install new commands  •  web updating  •  web file sharing  •  latest Stata news  

 

User-written commands

user-written commands for meta-analysis, data management, survival, econometrics

 

Programming features

adding new commands  •  command scripting  •  object-oriented programming  •  menu and dialog-box programming  •  Project Manager  •  plugins 

 

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 

 

Embedded statistical computations

Numerics by Stata

 

Installation Qualification

IQ report for regulatory agencies such as the FDA  •  installation verification

 

Accessibility

Section 508 compliance, accessibility for persons with disabilities

 

 
   
 
 

Complete data-management facilities

Stata's data-management features give you complete control of all types of data. 

You can combine and reshape datasets, manage variables, and collect statistics across groups or replicates. You can work with byte, integer, long, float, double, and string variables (including BLOBs and strings up to 2 billion characters). Stata also has advanced tools for managing specialized data such as survival/duration data, time-series data, panel/longitudinal data, categorical data, multiple-imputation data, and survey data.

 

 

Publication-quality graphics

   

 

Stata makes it easy to generate publication-quality, distinctly styled graphs. 

You can write scripts to produce hundreds or thousands of graphs in a reproducible manner and export them to EPS or TIF for publication, to PNG for the web, or to PDF for viewing. With the integrated Graph Editor you click to change anything about your graph or to add titles, notes, lines, arrows, and text.

 

Extensible

Stata is so programmable that developers and users add new features every day to respond to the growing demands of today's researchers.

With Stata's Internet capabilities, new features and official updates can be installed over the Internet with a single click.

 

Matrix programming with Mata

Mata is a full-blown programming language that compiles what you type into bytecode, optimizes it, and executes it fast. 

Though you don't need to program to use Stata, it is comforting to know that a fast and complete matrix programming language is an integral part of Stata. Mata is both an interactive environment for manipulating matrices and a full development environment that can produce compiled and optimized code. It includes special features for processing panel data, performs operations on real or complex matrices, provides complete support for object-oriented programming, and is fully integrated with every aspect of Stata.

 

Cross-platform compatible

Stata will run on Windows, Mac, and Linux/Unix computers; however, our licenses are not platform specific. 

That means if you have a Mac laptop and a Windows desktop, you don't need two separate licenses to run Stata. You can install your Stata license on any of the supported platforms. Stata datasets, programs, and other data can be shared across platforms without translation. You can also quickly and easily import datasets from other statistical packages, spreadsheets, and databases.

 

Trusted

Used by researchers for more than 30 years, Stata provides everything you need for data analysis, data management, and graphics.

 

 

 

 

 

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