Bayesian data analysis A Gelman, JB Carlin, HS Stern, DB Dunson, A Vehtari, DB Rubin CRC press | 13528 | | 2013 |

Inference from iterative simulation using multiple sequences A Gelman, DB Rubin Statistical science, 457-472 | 5076 | | 1992 |

Data analysis using regression and multilevel/hierarchical models A Gelman, J Hill Cambridge University Press | 3954 | | 2006 |

General methods for monitoring convergence of iterative simulations SP Brooks, A Gelman Journal of computational and graphical statistics 7 (4), 434-455 | 2110 | | 1998 |

Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper) A Gelman Bayesian analysis 1 (3), 515-534 | 1394 | | 2006 |

Posterior predictive assessment of model fitness via realized discrepancies A Gelman, XL Meng, H Stern Statistica sinica 6 (4), 733-760 | 1061 | | 1996 |

Hierarchical generalized linear models Y Lee, JA Nelder Journal of the Royal Statistical Society. Series B (Methodological), 619-678 | 734 | | 1996 |

R2WinBUGS: a package for running WinBUGS from R S Sturtz, U Ligges, AE Gelman Journal of Statistical software 12 (3), 1-16 | 706 | | 2005 |

Efficient metropolis jumping hules A Gelman, G Roberts, W Gilks Bayesian statistics 5, 599-608 | 692 | | 1996 |

Weak convergence and optimal scaling of random walk Metropolis algorithms GO Roberts, A Gelman, WR Gilks The annals of applied probability 7 (1), 110-120 | 682 | | 1997 |

Why are American presidential election campaign polls so variable when votes are so predictable? A Gelman, G King British Journal of Political Science 23 (04), 409-451 | 630 | | 1993 |

The EM Algorithm—an Old Folk‐song Sung to a Fast New Tune XL Meng, D Van Dyk Journal of the Royal Statistical Society: Series B (Statistical Methodology ... | 573 | | 1997 |

Simulating normalizing constants: From importance sampling to bridge sampling to path sampling A Gelman, XL Meng Statistical science, 163-185 | 554 | | 1998 |

Inference and monitoring convergence A Gelman Markov chain Monte Carlo in practice, 131-143 | 496 | | 1996 |

Estimating incumbency advantage without bias A Gelman, G King American Journal of Political Science, 1142-1164 | 428 | | 1990 |

Markov chain monte carlo in practice: A roundtable discussion RE Kass, BP Carlin, A Gelman, RM Neal The American Statistician 52 (2), 93-100 | 324 | | 1998 |

Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (Expanded Edition) A Gelman Princeton University Press | 293 | | 2009 |

A weakly informative default prior distribution for logistic and other regression models A Gelman, A Jakulin, MG Pittau, YS Su The Annals of Applied Statistics, 1360-1383 | 283 | | 2008 |

A smoothed EM approach to indirect estimation problems, with particular, reference to stereology and emission tomography BW Silverman, MC Jones, JD Wilson, DW Nychka Journal of the Royal Statistical Society. Series B (Methodological), 271-324 | 258 | | 1990 |

Spatial variability of arsenic in 6000 tube wells in a 25 km2 area of Bangladesh A Van Geen, Y Zheng, R Versteeg, M Stute, A Horneman, R Dhar, ... Water Resources Research 39 (5) | 243 | | 2003 |