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Home / Products / Stata 15

This page announced the new features in Stata 15. Please see our Stata 19 page for the new features in Stata 19.

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ERM = Endogeneity + Selection + Treatment Combine endogenous covariates, sample selection, and endogenous treatment in models for continuous, binary, ordered, and censored outcomes. Take your causal inference to a whole new level. Learn more »

Latent class analysis (LCA) Discover and understand the unobserved groupings in your data. Use LCA's model-based classification to find out how many groups you have, who is in those groups, and what makes those groups distinct. Learn more »

bayes: logistic ...and 44 more Type bayes: in front of any of 45 Stata estimation commands to fit a Bayesian regression model. Learn more »

Markdown & dynamic documents Type this, × Get this, Create webpages from Stata Intermix text, regressions, results, graphs, etc. See changes in data or commands automatically reflected on webpage Learn more »

Linearized DSGEs Write your model in simple algebraic form. Stata does the rest: solve model, estimate parameters, estimate policy and transition matrices (with CIs), estimate and graph IRFs, and perform forecasts. Learn more »

Finite mixture models (FMMs) 17 estimators and combinations Continuous, binary, count, ordinal, categorical, censored, and truncated outcomes Survival outcomes Learn more »

Spatial autoregressive models Because sometimes where you are matters. Learn more »

Interval-censored survival models Fit any of Stata's six parametric survival models to interval-censored data. All the usual survival features are supported: stratified estimation, robust and clustered SEs, survey data, graphs, and more. Learn more »

Nonlinear multilevelmixed-effects models When ... your science ... says ... your model ... is ... nonlinear in its parameters Learn more »

Mixed logit models: Advanced choice modeling Do you walk to work, ride a bus, or drive your car? Which of three insurance plans do you buy? Which political party do you vote for? We make dozens of choices every day. Researchers have access to gaggles of data about those choices. Mixed logit introduces random effects into choice modeling and thereby relaxes the IIA assumption and increases model flexibility. Learn more »

Nonparametric regression When you know something matters. But have no idea how. Learn more »

Create Word documents from Stata Automate your reports Write paragraphs and tables to Word documents Embed Stata results and graphs in paragraphs and tables Customize formatting of text, tables, and cells Learn more » Create PDFs, too!

Bayesian multilevel models × Small number of groups? Many hierarchical levels? Prefer making probability statements? Consider Bayesian multilevel modeling. Learn more »

Threshold regression Your time-series regression may change parameters at some point in time or at multiple points in time. The activity of foraging animals might follow a completely different pattern at temperatures above some threshold. You may not know the value of that threshold. Finding such thresholds and estimating the parameters within the regimes is what threshold regression does. Learn more »

Panel-data tobit with random coefficients Stata has long had estimators for random effects (random intercepts) in panel data. Now you can have random coefficients, too. Learn more »

Search, browse, and import FRED data The St. Louis Federal Reserve makes available over 470,000 U.S. and international economic and financial time series. You can now easily search, browse, and import these data. Learn more »

Multilevel regression for interval-measured outcomes Incomes are sometimes recorded in groupings, as are people's weights, insect counts, grade-point averages, and hundreds of other measures. Often we have repeated measurements for individuals, or schools, or orchards, etc. So ... we need multilevel regression for interval-measured (interval-censored) outcomes. Learn more »

Multilevel tobit regression for censored outcomes Left-censoring, right-censoring, both Censoring that varies by observation Make inferences about either the uncensored or the censored outcome Robust and clustered SEs Support for survey data Learn more »

Panel-data cointegration tests Tests Kao Pedroni Westerlund Total of nine variants of tests Learn more »

Tests for multiple breaks in time series Cumulative sum (CUSUM) test for parameter stability CUSUM of recursive residuals CUSUM of OLS residuals Plots with CIs Learn more »

Multiple-group generalized SEM Generalized SEM now supports multiple-group analysis. Easily specify groups and test parameter invariance across groups. GSEM models include continuous, binary, ordinal, count, categorical, and even survival outcomes multilevel models Learn more »

ICD-10-CM/PCS NCHS's ICD-10-CM diagnosis codes CMS's ICD-10-PCS procedure codes Verify codes are valid Create new variables based on codes Learn more »

Power for cluster randomized designs Power analysis for comparing One- and two-sample means One- and two-sample proportions Two-sample survivor curves when you randomize clusters instead of individuals Learn more »

Power for linear regression models × Solve for Power Sample size Effect size Specify lists of Alpha values Power levels Beta values Sample sizes And more Automated tables and graphs Learn more »

Heteroskedastic linear regression Model for the variance Robust and cluster SEs Survey-data support Learn more »

Poisson models with sample selection Counts are common. How many: Fish did you catch? Accidents occurred? Patents does a firm generate? Outcomes are not always seen. Folks evade the game warden. Accidents are not always reported. Some firms prefer trade secrets to patents. So you need Poisson models with sample selection. Learn more »

More in panel data Nonlinear models with random effects, including random coefficients Bayesian panel-data models Interval regression with random intercepts and random coefficients

More in graphics Transparency in graphs SVG export

More in statistics Bayesian survival models Zero-inflated ordered probit Add your own power and sample-size methods Bayesian sample-selection models And yet more

More in the interface Stata in Swedish Stata in Chinese Improvements to the Do-file Editor

And, even more Stream random-number generator Improvements for Java plugins

Of course, many of the new features are highly parallelized. Learn more »

You can learn about all of Stata and about all of Stata's features.

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