R package SASmixed: Data sets from ”SAS System for Mixed Models”. Data sets and sample lmer analyses corresponding to the examples in Littell, Milliken, Stroup and Wolfinger (1996), ”SAS System for Mixed Models”, SAS Institute.

References in zbMATH (referenced in 55 articles )

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  1. Fu, Liyong; Wang, Mingliang; Wang, Zuoheng; Song, Xinyu; Tang, Shouzheng: Maximum likelihood estimation of nonlinear mixed-effects models with crossed random effects by combining first-order conditional linearization and sequential quadratic programming (2019)
  2. Liu, Lei; Shih, Ya-Chen Tina; Strawderman, Robert L.; Zhang, Daowen; Johnson, Bankole A.; Chai, Haitao: Statistical analysis of zero-inflated nonnegative continuous data: a review (2019)
  3. Alicja Gosiewska; Przemyslaw Biecek: auditor: an R Package for Model-Agnostic Visual Validation and Diagnostic (2018) arXiv
  4. Kaya Bahçecitapar, Melike: Some factors affecting statistical power of approximate tests in the linear mixed model for longitudinal data (2018)
  5. Sofie Pødenphant, Kasper Kristensen, Per B. Brockhoff: The Multiplicative Mixed Model with the mumm R package as a General and Easy Random Interaction Model Tool (2018) arXiv
  6. Alexandra Kuznetsova; Per Brockhoff; Rune Christensen: lmerTest Package: Tests in Linear Mixed Effects Models (2017) not zbMATH
  7. Groll, Andreas; Tutz, Gerhard: Variable selection in discrete survival models including heterogeneity (2017)
  8. Powell, Christopher D.; López, Secundino; Dumas, André; Bureau, Dominique P.; Hook, Sarah E.; France, James: Mathematical descriptions of indeterminate growth (2017)
  9. Bailey, R. A.; Brien, C. J.: Randomization-based models for multitiered experiments. I: A chain of randomizations (2016)
  10. Forkman, Johannes: A comparison of super-valid restricted and row-column randomization (2016)
  11. Jaffa, Miran A.; Jaffa, Ayad A.: Joint modeling of covariates and censoring process assuming non-constant dropout hazard (2016)
  12. Munda, Marco; Legrand, Catherine; Duchateau, Luc; Janssen, Paul: Testing for decreasing heterogeneity in a new time-varying frailty model (2016)
  13. Wang, Wei: Identifiability of covariance parameters in linear mixed effects models (2016)
  14. Ishijima, Hiroshi; Maeda, Akira: Real estate pricing models: theory, evidence, and implementation (2015)
  15. Groll, Andreas; Tutz, Gerhard: Variable selection for generalized linear mixed models by (L_1)-penalized estimation (2014)
  16. Großmann, Heiko: Automating the analysis of variance of orthogonal designs (2014)
  17. Ulrich Halekoh; Søren Højsgaard: A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models - The R Package pbkrtest (2014) not zbMATH
  18. Ver Hoef, Jay M.; Cameron, Michael F.; Boveng, Peter L.; London, Josh M.; Moreland, Erin E.: A spatial hierarchical model for abundance of three ice-associated seal species in the eastern Bering Sea (2014)
  19. Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott: Moderation analysis using a two-level regression model (2014)
  20. Gallop, Robert J.; Rieger, Randall H.; McClintock, Scott; Atkins, David C.: A model for extreme stacking of data at endpoints of a distribution: illustration with W-shaped data (2013)

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