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Results 1 - 20 of 7,619,891  for All Library Resources

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1
Drivers, "Slow" Variables, "Fast" Variables, Shocks, and Resilience
Drivers, "Slow" Variables, "Fast" Variables, Shocks, and Resilience
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Drivers, "Slow" Variables, "Fast" Variables, Shocks, and Resilience

Ecology and society, 2012-01, Vol.17 (3), p.30-30, Article art30 [Peer Reviewed Journal]

Copyright © 2012 by the author(s) ;Copyright Resilience Alliance 2012 ;ISSN: 1708-3087 ;EISSN: 1708-3087 ;DOI: 10.5751/ES-05063-170330

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2
Testing Mediation and Suppression Effects of Latent Variables: Bootstrapping With Structural Equation Models
Testing Mediation and Suppression Effects of Latent Variables: Bootstrapping With Structural Equation Models
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Testing Mediation and Suppression Effects of Latent Variables: Bootstrapping With Structural Equation Models

Organizational research methods, 2008-04, Vol.11 (2), p.296-325 [Peer Reviewed Journal]

Copyright SAGE PUBLICATIONS, INC. Apr 2008 ;ISSN: 1094-4281 ;EISSN: 1552-7425 ;DOI: 10.1177/1094428107300343

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3
The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants' Ethical Decision Making
The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants' Ethical Decision Making
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The Role of Individual Variables, Organizational Variables and Moral Intensity Dimensions in Libyan Management Accountants' Ethical Decision Making

Journal of business ethics, 2016-03, Vol.134 (3), p.335-358 [Peer Reviewed Journal]

Springer Science+Business Media 2016 ;The Author(s) 2014 ;Springer Science+Business Media Dordrecht 2016 ;ISSN: 0167-4544 ;EISSN: 1573-0697 ;DOI: 10.1007/s10551-014-2421-3 ;CODEN: JBUEDJ

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4
Preanalytic Variables in Cytology: Lessons Learned From Next-Generation Sequencing-The MD Anderson Experience
Preanalytic Variables in Cytology: Lessons Learned From Next-Generation Sequencing-The MD Anderson Experience
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Preanalytic Variables in Cytology: Lessons Learned From Next-Generation Sequencing-The MD Anderson Experience

Archives of pathology & laboratory medicine (1976), 2016-11, Vol.140 (11), p.1191-1199 [Peer Reviewed Journal]

COPYRIGHT 2016 College of American Pathologists ;COPYRIGHT 2016 College of American Pathologists ;Copyright College of American Pathologists Nov 2016 ;ISSN: 0003-9985 ;ISSN: 1543-2165 ;EISSN: 1543-2165 ;DOI: 10.5858/arpa.2016-0117-ra ;PMID: 27333361 ;CODEN: APLMAS

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5
Errors-in-variables identification in dynamic networks — Consistency results for an instrumental variable approach
Errors-in-variables identification in dynamic networks — Consistency results for an instrumental variable approach
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Errors-in-variables identification in dynamic networks — Consistency results for an instrumental variable approach

Automatica (Oxford), 2015-12, Vol.62, p.39-50 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 0005-1098 ;EISSN: 1873-2836 ;DOI: 10.1016/j.automatica.2015.09.021

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6
Developing priority variables (“ecosystem Essential Ocean Variables” — eEOVs) for observing dynamics and change in Southern Ocean ecosystems
Developing priority variables (“ecosystem Essential Ocean Variables” — eEOVs) for observing dynamics and change in Southern Ocean ecosystems
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Developing priority variables (“ecosystem Essential Ocean Variables” — eEOVs) for observing dynamics and change in Southern Ocean ecosystems

Journal of marine systems, 2016-09, Vol.161 [Peer Reviewed Journal]

Attribution - NonCommercial - NoDerivatives ;ISSN: 0924-7963 ;EISSN: 1879-1573 ;DOI: 10.1016/j.jmarsys.2016.05.003

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7
Space-time variability of climate variables and intermittent renewable electricity production. A review
Space-time variability of climate variables and intermittent renewable electricity production. A review
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Space-time variability of climate variables and intermittent renewable electricity production. A review

Renewable & sustainable energy reviews, 2017-11, Vol.79, p.600-617 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1364-0321 ;EISSN: 1879-0690 ;DOI: 10.1016/j.rser.2017.05.046

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8
Why significant variables aren’t automatically good predictors
Why significant variables aren’t automatically good predictors
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Why significant variables aren’t automatically good predictors

Proceedings of the National Academy of Sciences - PNAS, 2015-11, Vol.112 (45), p.13892-13897 [Peer Reviewed Journal]

Volumes 1–89 and 106–112, copyright as a collective work only; author(s) retains copyright to individual articles ;Copyright National Academy of Sciences Nov 10, 2015 ;ISSN: 0027-8424 ;EISSN: 1091-6490 ;DOI: 10.1073/pnas.1518285112 ;PMID: 26504198

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9
Surfactant dynamics: hidden variables controlling fluid flows
Surfactant dynamics: hidden variables controlling fluid flows
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Surfactant dynamics: hidden variables controlling fluid flows

Journal of fluid mechanics, 2020-06, Vol.892, Article P1 [Peer Reviewed Journal]

The Author(s), 2020. Published by Cambridge University Press ;2020 This article is published under (https://creativecommons.org/licenses/by/3.0/) (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 0022-1120 ;EISSN: 1469-7645 ;DOI: 10.1017/jfm.2020.170 ;PMID: 33776139

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10
Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons
Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons
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Specialized coding of sensory, motor and cognitive variables in VTA dopamine neurons

Nature (London), 2019-06, Vol.570 (7762), p.509-513 [Peer Reviewed Journal]

COPYRIGHT 2019 Nature Publishing Group ;Copyright Nature Publishing Group Jun 27, 2019 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-019-1261-9 ;PMID: 31142844

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11
Host variables confound gut microbiota studies of human disease
Host variables confound gut microbiota studies of human disease
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Host variables confound gut microbiota studies of human disease

Nature (London), 2020-11, Vol.587 (7834), p.448-454 [Peer Reviewed Journal]

COPYRIGHT 2020 Nature Publishing Group ;Copyright Nature Publishing Group Nov 19, 2020 ;ISSN: 0028-0836 ;EISSN: 1476-4687 ;DOI: 10.1038/s41586-020-2881-9 ;PMID: 33149306

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12
High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models
High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models
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High Resolution Mapping of Soil Properties Using Remote Sensing Variables in South-Western Burkina Faso: A Comparison of Machine Learning and Multiple Linear Regression Models

PloS one, 2017-01, Vol.12 (1), p.e0170478-e0170478 [Peer Reviewed Journal]

COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Forkuor et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 Forkuor et al 2017 Forkuor et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0170478 ;PMID: 28114334

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13
Instrumental variables II: instrumental variable application—in 25 variations, the physician prescribing preference generally was strong and reduced covariate imbalance
Instrumental variables II: instrumental variable application—in 25 variations, the physician prescribing preference generally was strong and reduced covariate imbalance
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Instrumental variables II: instrumental variable application—in 25 variations, the physician prescribing preference generally was strong and reduced covariate imbalance

Journal of clinical epidemiology, 2009-12, Vol.62 (12), p.1233-1241 [Peer Reviewed Journal]

Elsevier Inc. ;2009 Elsevier Inc. ;2015 INIST-CNRS ;ISSN: 0895-4356 ;EISSN: 1878-5921 ;DOI: 10.1016/j.jclinepi.2008.12.006 ;PMID: 19345561

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14
Addressing Endogeneity Without Instrumental Variables: An Evaluation of the Gaussian Copula Approach for Management Research
Addressing Endogeneity Without Instrumental Variables: An Evaluation of the Gaussian Copula Approach for Management Research
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Addressing Endogeneity Without Instrumental Variables: An Evaluation of the Gaussian Copula Approach for Management Research

Journal of management, 2023-04, Vol.49 (4), p.1460-1495 [Peer Reviewed Journal]

The Author(s) 2022 ;ISSN: 0149-2063 ;EISSN: 1557-1211 ;DOI: 10.1177/01492063221085913

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15
A New Interpretation of the Period-Luminosity Sequences of Long-period Variables
A New Interpretation of the Period-Luminosity Sequences of Long-period Variables
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A New Interpretation of the Period-Luminosity Sequences of Long-period Variables

The Astrophysical journal, 2017-10, Vol.847 (2), p.139 [Peer Reviewed Journal]

2017. The American Astronomical Society. All rights reserved. ;Copyright IOP Publishing Oct 01, 2017 ;ISSN: 0004-637X ;EISSN: 1538-4357 ;DOI: 10.3847/1538-4357/aa8998

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16
ForestClim —Bioclimatic variables for microclimate temperatures of European forests
ForestClim —Bioclimatic variables for microclimate temperatures of European forests
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ForestClim —Bioclimatic variables for microclimate temperatures of European forests

Global change biology, 2023-06, Vol.29 (11), p.2886-2892 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1354-1013 ;EISSN: 1365-2486 ;DOI: 10.1111/gcb.16678

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17
The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH-MIDAS Approach
The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH-MIDAS Approach
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The Importance of the Macroeconomic Variables in Forecasting Stock Return Variance: A GARCH-MIDAS Approach

Journal of forecasting, 2013-11, Vol.32 (7), p.600-612 [Peer Reviewed Journal]

Copyright © 2013 John Wiley & Sons, Ltd. ;Copyright Wiley Periodicals Inc. Nov 2013 ;ISSN: 0277-6693 ;ISSN: 1099-131X ;EISSN: 1099-131X ;DOI: 10.1002/for.2256 ;CODEN: JOFODV

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18
On the RR Lyrae Stars in Globulars. V. The Complete Near-infrared (JHK s ) Census of ω Centauri RR Lyrae Variables
On the RR Lyrae Stars in Globulars. V. The Complete Near-infrared (JHK s ) Census of ω Centauri RR Lyrae Variables
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On the RR Lyrae Stars in Globulars. V. The Complete Near-infrared (JHK s ) Census of ω Centauri RR Lyrae Variables

The Astronomical journal, 2018-03, Vol.155 (3), p.137 [Peer Reviewed Journal]

Copyright IOP Publishing Mar 2018 ;ISSN: 0004-6256 ;EISSN: 1538-3881 ;DOI: 10.3847/1538-3881/aaadab

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19
Encoding high-cardinality string categorical variables
Encoding high-cardinality string categorical variables
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Encoding high-cardinality string categorical variables

IEEE transactions on knowledge and data engineering, 2022-03 [Peer Reviewed Journal]

Distributed under a Creative Commons Attribution 4.0 International License ;ISSN: 1041-4347 ;EISSN: 1558-2191 ;DOI: 10.1109/TKDE.2020.2992529

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20
Transforming variables to central normality
Transforming variables to central normality
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Transforming variables to central normality

Machine learning, 2021-03 [Peer Reviewed Journal]

ISSN: 0885-6125 ;EISSN: 1573-0565 ;DOI: 10.1007/s10994-021-05960-5

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