Stata is a complete, integrated statistical package that provides everything you need for data analysis, data management, and graphics. Stata is not sold in modules, which means you get everything you need in one package. And, you can choose a perpetual license, with nothing more to buy ever. Annual licenses are also available.Stata 12 adds many new features such as structural equation modeling (SEM), contrasts, ARFIMA, business calendars, chained equations for multiple imputation, contour plots, automatic memory management, importing and exporting of Excel files, and more. (Source:

References in zbMATH (referenced in 186 articles , 1 standard article )

Showing results 1 to 20 of 186.
Sorted by year (citations)

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  1. Canary, Jana D.; Blizzard, Leigh; Barry, Ronald P.; Hosmer, David W.; Quinn, Stephen J.: A comparison of the Hosmer-Lemeshow, Pigeon-Heyse, and Tsiatis goodness-of-fit tests for binary logistic regression under two grouping methods (2017)
  2. Donat, Francesco; Marra, Giampiero: Semi-parametric bivariate polychotomous ordinal regression (2017)
  3. Dudgeon, Paul: Some improvements in confidence intervals for standardized regression coefficients (2017)
  4. Francesco Bartolucci and Claudia Pigini: cquad: An R and Stata Package for Conditional Maximum Likelihood Estimation of Dynamic Binary Panel Data Models (2017)
  5. Haruvy, Ernan; Li, Sherry Xin; McCabe, Kevin; Twieg, Peter: Communication and visibility in public goods provision (2017)
  6. Inmaculada Álvarez and Javier Barbero and José Zofío: A Panel Data Toolbox for MATLAB (2017)
  7. Jeremy Ferwerda and Jens Hainmueller and Chad Hazlett: Kernel-Based Regularized Least Squares in R (KRLS) and Stata (krls) (2017)
  8. Liu, Jia; Riyanto, Yohanes E.: Information transparency and equilibrium selection in coordination games: an experimental study (2017)
  9. Manly, Bryan F. J.; Navarro Alberto, Jorge A.: Multivariate statistical methods. A primer (2017)
  10. Marra, Giampiero; Radice, Rosalba: A joint regression modeling framework for analyzing bivariate binary data in $\mathsfR$ (2017)
  11. Riccardo Lucchetti and Claudia Pigini: DPB: Dynamic Panel Binary Data Models in gretl (2017)
  12. Suárez, Erick; Pérez, Cynthia M.; Rivera, Roberto; Martínez, Melissa N.: Applications of regression models in epidemiology (2017)
  13. Yujing Jiang, Xin He, Mei-Ling Ting Lee, Bernard Rosner, Jun Yan: Wilcoxon Rank-Based Tests for Clustered Data with R Package clusrank (2017) arXiv
  14. Acock, Alan C.: A gentle introduction to Stata (2016)
  15. Bartolucci, Francesco; Bacci, Silvia; Gnaldi, Michela: Statistical analysis of questionnaires. A unified approach based on R and Stata (2016)
  16. Bertanha, Marinho; Moser, Petra: Spatial errors in count data regressions (2016)
  17. Fullerton, Andrew S.; Xu, Jun: Ordered regression models. Parallel, partial, and non-parallel alternatives (2016)
  18. Giannelli, Gianna Claudia; Rapallini, Chiara: Immigrant student performance in math: does it matter where you come from? (2016) MathEduc
  19. Hilbe, Joseph M.: Practical guide to logistic regression (2016)
  20. Isidro, Marissa; Haslett, Stephen; Jones, Geoff: Extended structure preserving estimation (ESPREE) for updating small area estimates of poverty (2016)

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