Bayesian data analysis, 3rd edition A Gelman, JB Carlin, HS Stern, DB Dunson, A Vehtari, DB Rubin Chapman & Hall/CRC, 2013 | 38985* | 2013 |

Inference from iterative simulation using multiple sequences A Gelman, DB Rubin Statistical science 7 (4), 457-472, 1992 | 18931 | 1992 |

Data analysis using regression and multilevel/hierarchical models A Gelman Cambridge University Press, 2007 | 18833 | 2007 |

General methods for monitoring convergence of iterative simulations SP Brooks, A Gelman Journal of computational and graphical statistics 7 (4), 434-455, 1998 | 7912 | 1998 |

Stan: A probabilistic programming language B Carpenter, A Gelman, MD Hoffman, D Lee, B Goodrich, M Betancourt, ... Journal of statistical software 76, 2017 | 7886 | 2017 |

Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper) A Gelman | 5526 | 2006 |

The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. MD Hoffman, A Gelman J. Mach. Learn. Res. 15 (1), 1593-1623, 2014 | 5468 | 2014 |

Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC A Vehtari, A Gelman, J Gabry Statistics and computing 27, 1413-1432, 2017 | 4861 | 2017 |

Handbook of markov chain monte carlo S Brooks, A Gelman, G Jones, XL Meng CRC press, 2011 | 3448 | 2011 |

Posterior predictive assessment of model fitness via realized discrepancies A Gelman, XL Meng, H Stern Statistica sinica, 733-760, 1996 | 3021 | 1996 |

Scaling regression inputs by dividing by two standard deviations A Gelman Statistics in medicine 27 (15), 2865-2873, 2008 | 2596 | 2008 |

Weak convergence and optimal scaling of random walk Metropolis algorithms A Gelman, WR Gilks, GO Roberts The annals of applied probability 7 (1), 110-120, 1997 | 2404 | 1997 |

A weakly informative default prior distribution for logistic and other regression models A Gelman, A Jakulin, MG Pittau, YS Su | 2319 | 2008 |

Understanding predictive information criteria for Bayesian models A Gelman, J Hwang, A Vehtari Statistics and computing 24, 997-1016, 2014 | 2262 | 2014 |

Why high-order polynomials should not be used in regression discontinuity designs A Gelman, G Imbens Journal of Business & Economic Statistics 37 (3), 447-456, 2019 | 2086 | 2019 |

R2WinBUGS: a package for running WinBUGS from R S Sturtz, U Ligges, A Gelman Journal of Statistical software 12, 1-16, 2005 | 2067 | 2005 |

Efficient Metropolis jumping rules A Gelman, GO Roberts, WR Gilks Bayesian statistics 5 (599-608), 42, 1996 | 1593 | 1996 |

Why we (usually) don't have to worry about multiple comparisons A Gelman, J Hill, M Yajima Journal of research on educational effectiveness 5 (2), 189-211, 2012 | 1489 | 2012 |

Beyond power calculations: Assessing type S (sign) and type M (magnitude) errors A Gelman, J Carlin Perspectives on psychological science 9 (6), 641-651, 2014 | 1396 | 2014 |

The difference between “significant” and “not significant” is not itself statistically significant A Gelman, H Stern The American Statistician 60 (4), 328-331, 2006 | 1311 | 2006 |