References in zbMATH (referenced in 217 articles , 1 standard article )

Showing results 1 to 20 of 217.
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  1. Scutari, Marco; Denis, Jean-Baptiste: Bayesian networks. With examples in R (2022)
  2. Adrian Richter; Carsten Oliver Schmidt; Markus Krüger; Stephan Struckmann: dataquieR: assessment of data quality in epidemiological research (2021) not zbMATH
  3. Alex Stringer: Implementing Adaptive Quadrature for Bayesian Inference: the aghq Package (2021) arXiv
  4. Cochrane, Courtney; Ba, Demba; Klerman, Elizabeth B.; St. Hilaire, Melissa A.: An ensemble mixed effects model of sleep loss and performance (2021)
  5. Eshin Jolly: Pymer4: Connecting R and Python for Linear Mixed Modeling (2021) not zbMATH
  6. Ferri-García, Ramón; Castro-Martín, Luis; del Mar Rueda, María: Evaluating machine learning methods for estimation in online surveys with superpopulation modeling (2021)
  7. Hoff, Peter: Additive and multiplicative effects network models (2021)
  8. Hu, Xinyu; Qian, Min; Cheng, Bin; Cheung, Ying Kuen: Personalized policy learning using longitudinal mobile health data (2021)
  9. Jiang, Yingda; Chiu, Chi-Yang; Yan, Qi; Chen, Wei; Gorin, Michael B.; Conley, Yvette P.; Lakhal-Chaieb, M’Hamed Lajmi; Cook, Richard J.; Amos, Christopher I.; Wilson, Alexander F.; Bailey-Wilson, Joan E.; McMahon, Francis J.; Vazquez, Ana I.; Yuan, Ao; Zhong, Xiaogang; Xiong, Momiao; Weeks, Daniel E.; Fan, Ruzong: Gene-based association testing of dichotomous traits with generalized functional linear mixed models using extended pedigrees: applications to age-related macular degeneration (2021)
  10. Manju, Md Abu; Candel, Math J. J. M.; van Breukelen, Gerard J. P.: Robustness of cost-effectiveness analyses of cluster randomized trials assuming bivariate normality against skewed cost data (2021)
  11. Sugasawa, Shonosuke: Grouped heterogeneous mixture modeling for clustered data (2021)
  12. Thomas, Abin; Vishwakarma, Gajendra K.; Bhattacharjee, Atanu: Joint modeling of longitudinal and time-to-event data on multivariate protein biomarkers (2021)
  13. Wollschläger, Daniel: R compact. The fast introduction into data analysis (2021)
  14. Yunyi Shen, Claudia Solis-Lemus: CARlasso: An R package for the estimation of sparse microbial networks with predictors (2021) arXiv
  15. Aaron Cochrane: TEfits: Nonlinear regression for time-evolving indices (2020) not zbMATH
  16. Achim Zeileis, Susanne Köll, Nathaniel Graham: Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R (2020) not zbMATH
  17. Barkley, Brian G.; Hudgens, Michael G.; Clemens, John D.; Ali, Mohammad; Emch, Michael E.: Causal inference from observational studies with clustered interference, with application to a cholera vaccine study (2020)
  18. Bradley, Jonathan R.; Holan, Scott H.; Wikle, Christopher K.: Bayesian hierarchical models with conjugate full-conditional distributions for dependent data from the natural exponential family (2020)
  19. Cho, Sun-Joo; Brown-Schmidt, Sarah; De Boeck, Paul; Shen, Jianhong: Modeling intensive polytomous time-series eye-tracking data: a dynamic tree-based item response model (2020)
  20. Christen, J. Andrés; Parker, Albert E.: Systematic statistical analysis of microbial data from dilution series (2020)

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