SAS/STAT

SAS/STAT software, a component of the SAS System, provides comprehensive statistical tools for a wide range of statistical analyses, including analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster analysis, and nonparametric analysis. A few examples include mixed models, generalized linear models, correspondence analysis, and structural equations.


References in zbMATH (referenced in 264 articles )

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  1. Alberto Garcia-Hernandez; Dimitris Rizopoulos: %JM: A SAS Macro to Fit Jointly Generalized Mixed Models for Longitudinal Data and Time-to-Event Responses (2018)
  2. Bergtold, Jason S.; Pokharel, Krishna P.; Featherstone, Allen M.; Mo, Lijia: On the examination of the reliability of statistical software for estimating regression models with discrete dependent variables (2018)
  3. Heinze, Georg; Wallisch, Christine; Dunkler, Daniela: Variable selection - A review and recommendations for the practicing Statistician (2018)
  4. Jingyi Guo; Andrea Riebler: meta4diag: Bayesian Bivariate Meta-Analysis of Diagnostic Test Studies for Routine Practice (2018)
  5. Jing Zhao; Jian’an Luan; Peter Congdon: Bayesian Linear Mixed Models with Polygenic Effects (2018)
  6. Kaya Bahçecitapar, Melike: Some factors affecting statistical power of approximate tests in the linear mixed model for longitudinal data (2018)
  7. Ma, Zhihua; Chen, Guanghui: Bayesian methods for dealing with missing data problems (2018)
  8. Steffen, Kyle R.; Epshteyn, Yekaterina; Zhu, Jingyi; Bowler, Megan J.; Deming, Jody W.; Golden, Kenneth M.: Network modeling of fluid transport through sea ice with entrained exopolymeric substances (2018)
  9. Worku, Hailemichael M.; de Rooij, Mark: A multivariate logistic distance model for the analysis of multiple binary responses (2018)
  10. Wyszynski, Karol; Marra, Giampiero: Sample selection models for count data in R (2018)
  11. Clifford Anderson-Bergman: icenReg: Regression Models for Interval Censored Data in R (2017)
  12. Dey, Sanku; Mazucheli, Josmar; Anis, M. Z.: Estimation of reliability of multicomponent stress-strength for a Kumaraswamy distribution (2017)
  13. Filipiak, Katarzyna; Klein, Daniel; Roy, Anuradha: A comparison of likelihood ratio tests and Rao’s score test for three separable covariance matrix structures (2017)
  14. Ford, Whitney P.; Westgate, Philip M.: Improved standard error estimator for maintaining the validity of inference in cluster randomized trials with a small number of clusters (2017)
  15. Lewis, Taylor H.: Complex survey data analysis with SAS (2017)
  16. Powell, Christopher D.; López, Secundino; Dumas, André; Bureau, Dominique P.; Hook, Sarah E.; France, James: Mathematical descriptions of indeterminate growth (2017)
  17. Raol, Jitendra R.; Gopalratnam, Girija; Twala, Bhekisipho: Nonlinear filtering. Concepts and engineering applications. (2017)
  18. Staggs, Vincent S.: Comparison of naïve, Kenward-Roger, and parametric bootstrap interval approaches to small-sample inference in linear mixed models (2017)
  19. Yuan, Ke-Hai; Bentler, Peter M.: Improving the convergence rate and speed of Fisher-scoring algorithm: ridge and anti-ridge methods in structural equation modeling (2017)
  20. Bailey, R. A.; Brien, C. J.: Randomization-based models for multitiered experiments. I: A chain of randomizations (2016)

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