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.
Keywords for this software
References in zbMATH (referenced in 403 articles )
Showing results 1 to 20 of 403.
Sorted by year (- Komaroff, Eugene: Relationships between (p)-values and Pearson correlation coefficients, type 1 errors and effect size errors, under a true null hypothesis (2020)
- Lyles, Robert H.; Weiss, Paul; Waller, Lance A.: Calibrated Bayesian credible intervals for binomial proportions (2020)
- Rainer Hirk, Kurt Hornik, Laura Vana: mvord: An R Package for Fitting Multivariate Ordinal Regression Models (2020) not zbMATH
- Vo-Thanh, Nha; Piepho, Hans-Peter: Augmented quasi-sudoku designs in field trials (2020)
- Alnosaier, Waseem; Birkes, David: Inner workings of the Kenward-Roger test (2019)
- Daniel Sabanés Bové, Wai Yin Yeung, Giuseppe Palermo, Thomas Jaki: Model-Based Dose Escalation Designs in R with crmPack (2019) not zbMATH
- Lohr, Sharon L.: Sampling. Design and analysis (2019)
- Meulman, Jacqueline J.; van der Kooij, Anita J.; Duisters, Kevin L. W.: ROS regression: integrating regularization with optimal scaling regression (2019)
- Paolella, Marc S.: Linear models and time-series analysis. Regression, ANOVA, ARMA and GARCH (2019)
- Payne, Scott; Fuller, Edgar; Zhang, Cun-Quan: Edge-cuts of optimal average weights (2019)
- Powell, Christopher D.; López, Secundino; France, James: Elementary functions modified for seasonal effects to describe growth in freshwater fish (2019)
- Preisser, John S.; Inan, Gul; Powers, James M.; Chu, Haitao: A population-averaged approach to diagnostic test meta-analysis (2019)
- Theodor Balan; Hein Putter: frailtyEM: An R Package for Estimating Semiparametric Shared Frailty Models (2019) not zbMATH
- Xu, Shizhong: An alternative derivation of Harville’s restricted log likelihood function for variance component estimation (2019)
- Alberto Garcia-Hernandez; Dimitris Rizopoulos: %JM: A SAS Macro to Fit Jointly Generalized Mixed Models for Longitudinal Data and Time-to-Event Responses (2018) not zbMATH
- Arabameri, Abazar; Asemani, Davud; Hadjati, Jamshid: A structural methodology for modeling immune-tumor interactions including pro- and anti-tumor factors for clinical applications (2018)
- 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)
- Castilla, Elena; Martín, Nirian; Pardo, Leandro: Minimum phi-divergence estimators for multinomial logistic regression with complex sample design (2018)
- 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
- Fumes-Ghantous, Giovana; Ferrari, Silvia L. P.; Corrente, José Eduardo: Box-Cox (t) random intercept model for estimating usual nutrient intake distributions (2018)