Institution
York University
Education•Toronto, Ontario, Canada•
About: York University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Poison control. The organization has 18899 authors who have published 43357 publications receiving 1568560 citations.
Topics: Population, Poison control, Large Hadron Collider, Politics, Galaxy
Papers published on a yearly basis
Papers
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TL;DR: A convenient, although not comprehensive, presentation of required sample sizes is providedHere the sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests.
Abstract: One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
38,291 citations
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TL;DR: In this article, the authors present a procedure for having two or more judges independently categorize a sample of units and determine the degree, significance, and significance of the units. But they do not discuss the extent to which these judgments are reproducible, i.e., reliable.
Abstract: CONSIDER Table 1. It represents in its formal characteristics a situation which arises in the clinical-social-personality areas of psychology, where it frequently occurs that the only useful level of measurement obtainable is nominal scaling (Stevens, 1951, pp. 2526), i.e. placement in a set of k unordered categories. Because the categorizing of the units is a consequence of some complex judgment process performed by a &dquo;two-legged meter&dquo; (Stevens, 1958), it becomes important to determine the extent to which these judgments are reproducible, i.e., reliable. The procedure which suggests itself is that of having two (or more) judges independently categorize a sample of units and determine the degree, significance, and
34,965 citations
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01 Jan 1975TL;DR: In this article, the Mathematical Basis for Multiple Regression/Correlation and Identification of the Inverse Matrix Elements is presented. But it does not address the problem of missing data.
Abstract: Contents: Preface. Introduction. Bivariate Correlation and Regression. Multiple Regression/Correlation With Two or More Independent Variables. Data Visualization, Exploration, and Assumption Checking: Diagnosing and Solving Regression Problems I. Data-Analytic Strategies Using Multiple Regression/Correlation. Quantitative Scales, Curvilinear Relationships, and Transformations. Interactions Among Continuous Variables. Categorical or Nominal Independent Variables. Interactions With Categorical Variables. Outliers and Multicollinearity: Diagnosing and Solving Regression Problems II. Missing Data. Multiple Regression/Correlation and Causal Models. Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model. Random Coefficient Regression and Multilevel Models. Longitudinal Regression Methods. Multiple Dependent Variables: Set Correlation. Appendices: The Mathematical Basis for Multiple Regression/Correlation and Identification of the Inverse Matrix Elements. Determination of the Inverse Matrix and Applications Thereof.
29,764 citations
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TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.
9,282 citations
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TL;DR: The Kw provides for the incorpation of ratio-scaled degrees of disagreement (or agreement) to each of the cells of the k * k table of joi.
Abstract: A previously described coefficient of agreement for nominal scales, kappa, treats all disagreements equally. A generalization to weighted kappa (Kw) is presented. The Kw provides for the incorpation of ratio-scaled degrees of disagreement (or agreement) to each of the cells of the k * k table of joi
7,604 citations
Authors
Showing all 19301 results
Name | H-index | Papers | Citations |
---|---|---|---|
David W. Hogg | 130 | 468 | 106725 |
Alexander Khanov | 129 | 1219 | 87089 |
Yann Coadou | 129 | 960 | 79907 |
Dugan O'Neil | 128 | 1000 | 80700 |
Oliver Stelzer-Chilton | 128 | 1141 | 79154 |
David N. Spergel | 128 | 723 | 119714 |
Isabel Marian Trigger | 128 | 974 | 77594 |
Erich Varnes | 128 | 1180 | 75959 |
Rolf Seuster | 128 | 770 | 72369 |
Reda Tafirout | 128 | 999 | 82433 |
Carlos Avila | 125 | 1606 | 86581 |
Benjamin D. Wandelt | 123 | 530 | 99443 |
Clive Dickinson | 123 | 501 | 80701 |
Michael L. Dustin | 122 | 470 | 60499 |
David Ron | 119 | 298 | 80414 |