SAS

SAS (Statistical Analysis System) is an integrated system of software products provided by SAS Institute Inc.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 1225 articles , 2 standard articles )

Showing results 1 to 20 of 1225.
Sorted by year (citations)

1 2 3 ... 60 61 62 next

  1. Chang, Mark; Balser, John; Roach, Jim; Bliss, Robin: Innovative strategies, statistical solutions and simulations for modern clinical trials (2019)
  2. Christine Harvey; R. S. Weigel: Transplant2Mongo: Python Scripts that Insert Organ Procurement and Transplantation Network (OPTN) Data in MongoDB (2019) not zbMATH
  3. Djeundje, Viani Biatat; Crook, Jonathan: Dynamic survival models with varying coefficients for credit risks. (2019)
  4. Korosteleva, Olga: Advanced regression models with SAS and R (2019)
  5. Manju, Md Abu; Candel, Math J. J. M.; van Breukelen, Gerard J. P.: SamP2Cet: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials (2019)
  6. McCarthy, Richard V.; McCarthy, Mary M.; Ceccucci, Wendy; Halawi, Leila: Applying predictive analytics. Finding value in data (2019)
  7. Powell, Christopher D.; López, Secundino; France, James: Elementary functions modified for seasonal effects to describe growth in freshwater fish (2019)
  8. Preisser, John S.; Inan, Gul; Powers, James M.; Chu, Haitao: A population-averaged approach to diagnostic test meta-analysis (2019)
  9. Shieh, Gwowen: Effect size, statistical power, and sample size for assessing interactions between categorical and continuous variables (2019)
  10. Thomas Jaki; Philip Pallmann; Dominic Magirr: The R Package MAMS for Designing Multi-Arm Multi-Stage Clinical Trials (2019) not zbMATH
  11. Xu, Shizhong: An alternative derivation of Harville’s restricted log likelihood function for variance component estimation (2019)
  12. Yiyun Shou and Michael Smithson: cdfquantreg: An R Package for CDF-Quantile Regression (2019) not zbMATH
  13. Agresti, Alan: An introduction to categorical data analysis (2018)
  14. Arabameri, Abazar; Asemani, Davud; Hadjati, Jamshid: A structural methodology for modeling immune-tumor interactions including pro- and anti-tumor factors for clinical applications (2018)
  15. 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)
  16. Chanialidis, Charalampos; Evers, Ludger; Neocleous, Tereza; Nobile, Agostino: Efficient Bayesian inference for COM-Poisson regression models (2018)
  17. Chan, Priscilla H.; Xu, Ronghui; Chambers, Christina D.: A study of (R^2) measure under the accelerated failure time models (2018)
  18. Chow, Sy-Miin; Ou, Lu; Ciptadi, Arridhana; Prince, Emily B.; You, Dongjun; Hunter, Michael D.; Rehg, James M.; Rozga, Agata; Messinger, Daniel S.: Representing sudden shifts in intensive dyadic interaction data using differential equation models with regime switching (2018)
  19. Daniela Dunkler; Meinhard Ploner; Michael Schemper; Georg Heinze: Weighted Cox Regression Using the R Package coxphw (2018) not zbMATH
  20. Delia Voronca; Mulugeta Gebregziabher; Valerie Durkalski-Mauldin; Lei Liu; Leonard Egede: MTPmle: A SAS Macro and Stata Programs for Marginalized Inference in Semi-Continuous Data (2018) not zbMATH

1 2 3 ... 60 61 62 next


Further publications can be found at: http://support.sas.com/resources/papers/index.html