Institution
University of Amsterdam
Education•Amsterdam, Noord-Holland, Netherlands•
About: University of Amsterdam is a education organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 59309 authors who have published 140894 publications receiving 5984137 citations. The organization is also known as: UvA & Universiteit van Amsterdam.
Papers published on a yearly basis
Papers
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TL;DR: The use of standards for the measurement of photoluminescence quantum yields (QYs) in dilute solutions is reviewed in this paper, where only three standards can be considered well-founded.
Abstract: The use of standards for the measurement of photoluminescence quantum yields (QYs) in dilute solutions is reviewed. Only three standards can be considered well estab- lished. Another group of six standards has been investigated by several independent researchers. A large group of standards is frequently used in recent literature, but the valid- ity of these is less certain. The needs for future development comprise: (i) confirmation of the validity of the QY values of many commonly used standard materials, preferably in the form of SI traceable standards; (ii) extension of the set of standard materials to the UV and near-IR spectral ranges; and (iii) good standards or robust protocols for the measurements of low QYs.
1,592 citations
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University of Southern California1, Duke University2, Stockholm School of Economics3, Center for Open Science4, University of Virginia5, University of Amsterdam6, University of Pennsylvania7, University of North Carolina at Chapel Hill8, University of Regensburg9, California Institute of Technology10, New York University11, Research Institute of Industrial Economics12, Cardiff University13, Mathematica Policy Research14, Northwestern University15, Ohio State University16, University of Sussex17, Texas A&M University18, Royal Holloway, University of London19, University of Zurich20, University of Melbourne21, University of Wisconsin-Madison22, University of Michigan23, Stanford University24, Rutgers University25, Columbia University26, University of Washington27, University of Edinburgh28, National University of Singapore29, Utrecht University30, Arizona State University31, Princeton University32, University of California, Los Angeles33, Imperial College London34, University of Innsbruck35, Harvard University36, University of Chicago37, University of Pittsburgh38, University of Notre Dame39, University of California, Berkeley40, Johns Hopkins University41, University of Bristol42, University of New South Wales43, Dartmouth College44, Whitman College45, University of Puerto Rico46, University of Milan47, University of California, Irvine48, Paris Dauphine University49, University of British Columbia50, Ludwig Maximilian University of Munich51, Purdue University52, Washington University in St. Louis53, University of California, Davis54, Microsoft55
TL;DR: The default P-value threshold for statistical significance is proposed to be changed from 0.05 to 0.005 for claims of new discoveries in order to reduce uncertainty in the number of discoveries.
Abstract: We propose to change the default P-value threshold for statistical significance from 0.05 to 0.005 for claims of new discoveries.
1,586 citations
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TL;DR: In this article, the authors introduce the current state-of-the-art of network estimation and propose two novel statistical methods: the correlation stability coefficient and the bootstrapped difference test for edge-weights and centrality indices.
Abstract: The usage of psychological networks that conceptualize behavior as a complex interplay of psychological and other components has gained increasing popularity in various research fields. While prior publications have tackled the topics of estimating and interpreting such networks, little work has been conducted to check how accurate (i.e., prone to sampling variation) networks are estimated, and how stable (i.e., interpretation remains similar with less observations) inferences from the network structure (such as centrality indices) are. In this tutorial paper, we aim to introduce the reader to this field and tackle the problem of accuracy under sampling variation. We first introduce the current state-of-the-art of network estimation. Second, we provide a rationale why researchers should investigate the accuracy of psychological networks. Third, we describe how bootstrap routines can be used to (A) assess the accuracy of estimated network connections, (B) investigate the stability of centrality indices, and (C) test whether network connections and centrality estimates for different variables differ from each other. We introduce two novel statistical methods: for (B) the correlation stability coefficient, and for (C) the bootstrapped difference test for edge-weights and centrality indices. We conducted and present simulation studies to assess the performance of both methods. Finally, we developed the free R-package bootnet that allows for estimating psychological networks in a generalized framework in addition to the proposed bootstrap methods. We showcase bootnet in a tutorial, accompanied by R syntax, in which we analyze a dataset of 359 women with posttraumatic stress disorder available online.
1,584 citations
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TL;DR: The utility of P3 amplitude as a sensitive and diagnostic measure of processing capacity remains limited because the two principal task variables that have been used to manipulate capacity allocation have opposite effects on the amplitude.
Abstract: The present review focuses on the utility of the amplitude of P3 of as a measure of processing capacity and mental workload. The paper starts with a brief outline of the conceptual framework underlying the relationship between P3 amplitude and task demands, and the cognitive task manipulations that determine demands on capacity. P3 amplitude results are then discussed on the basis of an extensive review of the relevant literature. It is concluded that although it has often been assumed that P3 amplitude depends on the capacity for processing task relevant stimuli, the utility of P3 amplitude as a sensitive and diagnostic measure of processing capacity remains limited. The major factor that prompts this conclusion is that the two principal task variables that have been used to manipulate capacity allocation, namely task difficulty and task emphasis, have opposite effects on the amplitude of P3. I suggest that this is because, in many tasks, an increase in difficulty transforms the structure or actual content of the flow of information in the processing systems, thereby interfering with the very processes that underlie P3 generation. Finally, in an attempt to theoretically integrate the results of the reviewed studies, it is proposed that P3 amplitude reflects activation of elements in a event-categorization network that is controlled by the joint operation of attention and working memory.
1,577 citations
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TL;DR: The number of adults with raised blood pressure increased from 594 million in 1975 to 1·13 billion in 2015, with the increase largely in low-income and middle-income countries, and the contributions of changes in prevalence versus population growth and ageing to the increase.
1,573 citations
Authors
Showing all 59759 results
Name | H-index | Papers | Citations |
---|---|---|---|
Richard A. Flavell | 231 | 1328 | 205119 |
Scott M. Grundy | 187 | 841 | 231821 |
Stuart H. Orkin | 186 | 715 | 112182 |
Kenneth C. Anderson | 178 | 1138 | 126072 |
David A. Weitz | 178 | 1038 | 114182 |
Dorret I. Boomsma | 176 | 1507 | 136353 |
Brenda W.J.H. Penninx | 170 | 1139 | 119082 |
Michael Kramer | 167 | 1713 | 127224 |
Nicholas J. White | 161 | 1352 | 104539 |
Lex M. Bouter | 158 | 767 | 103034 |
Wolfgang Wagner | 156 | 2342 | 123391 |
Jerome I. Rotter | 156 | 1071 | 116296 |
David Cella | 156 | 1258 | 106402 |
David Eisenberg | 156 | 697 | 112460 |
Naveed Sattar | 155 | 1326 | 116368 |