Institution

# University of Chicago

Education•Chicago, Illinois, United States•

About: University of Chicago is a education organization based out in Chicago, Illinois, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 66716 authors who have published 160098 publications receiving 9644339 citations. The organization is also known as: Chicago University & U of C.

Topics: Population, Galaxy, Cancer, Transplantation, Poison control

##### Papers published on a yearly basis

##### Papers

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TL;DR: In this article, the product-limit (PL) estimator was proposed to estimate the proportion of items in the population whose lifetimes would exceed t (in the absence of such losses), without making any assumption about the form of the function P(t).

Abstract: In lifetesting, medical follow-up, and other fields the observation of the time of occurrence of the event of interest (called a death) may be prevented for some of the items of the sample by the previous occurrence of some other event (called a loss). Losses may be either accidental or controlled, the latter resulting from a decision to terminate certain observations. In either case it is usually assumed in this paper that the lifetime (age at death) is independent of the potential loss time; in practice this assumption deserves careful scrutiny. Despite the resulting incompleteness of the data, it is desired to estimate the proportion P(t) of items in the population whose lifetimes would exceed t (in the absence of such losses), without making any assumption about the form of the function P(t). The observation for each item of a suitable initial event, marking the beginning of its lifetime, is presupposed. For random samples of size N the product-limit (PL) estimate can be defined as follows: L...

52,450 citations

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TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.

24,874 citations

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03 Mar 1992TL;DR: The Logic of Hierarchical Linear Models (LMLM) as discussed by the authors is a general framework for estimating and hypothesis testing for hierarchical linear models, and it has been used in many applications.

Abstract: Introduction The Logic of Hierarchical Linear Models Principles of Estimation and Hypothesis Testing for Hierarchical Linear Models An Illustration Applications in Organizational Research Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known Three-Level Models Assessing the Adequacy of Hierarchical Models Technical Appendix

23,126 citations

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Oregon Health & Science University

^{1}, College of American Pathologists^{2}, Boston Children's Hospital^{3}, GeneDx^{4}, Medical College of Wisconsin^{5}, University of Chicago^{6}, University of California, Los Angeles^{7}, Emory University^{8}, University of Utah^{9}, University of Colorado Denver^{10}, Harvard University^{11}TL;DR: Because of the increased complexity of analysis and interpretation of clinical genetic testing described in this report, the ACMG strongly recommends thatclinical molecular genetic testing should be performed in a Clinical Laboratory Improvement Amendments–approved laboratory, with results interpreted by a board-certified clinical molecular geneticist or molecular genetic pathologist or the equivalent.

17,834 citations

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TL;DR: In this article, the authors consider the prospects for constructing a neoclassical theory of growth and international trade that is consistent with some of the main features of economic development, and compare three models and compared to evidence.

16,965 citations

##### Authors

Showing all 67909 results

Name | H-index | Papers | Citations |
---|---|---|---|

George M. Whitesides | 240 | 1739 | 269833 |

Solomon H. Snyder | 232 | 1222 | 200444 |

Eugene Braunwald | 230 | 1711 | 264576 |

Kari Stefansson | 206 | 794 | 174819 |

Hagop M. Kantarjian | 204 | 3708 | 210208 |

David Miller | 203 | 2573 | 204840 |

Martin White | 196 | 2038 | 232387 |

Craig B. Thompson | 195 | 557 | 173172 |

Robert C. Nichol | 187 | 851 | 162994 |

Jing Wang | 184 | 4046 | 202769 |

Patrick O. Brown | 183 | 755 | 200985 |

Yusuke Nakamura | 179 | 2076 | 160313 |

H. S. Chen | 179 | 2401 | 178529 |

Joseph Biederman | 179 | 1012 | 117440 |

Daniel J. Eisenstein | 179 | 672 | 151720 |