Dissociable psychosocial profiles of adolescent substance users
Author
Abstract
Suggested Citation
DOI: 10.1371/journal.pone.0202498
Download full text from publisher
References listed on IDEAS
- John P A Ioannidis, 2005. "Why Most Published Research Findings Are False," PLOS Medicine, Public Library of Science, vol. 2(8), pages 1-1, August.
- Takaya Saito & Marc Rehmsmeier, 2015. "The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
- Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
- Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
- Wei-Hsuan Lo-Ciganic & James L Huang & Hao H Zhang & Jeremy C Weiss & C Kent Kwoh & Julie M Donohue & Adam J Gordon & Gerald Cochran & Daniel C Malone & Courtney C Kuza & Walid F Gellad, 2020. "Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-16, July.
- Merlijn Breugel & Cancan Qi & Zhongli Xu & Casper-Emil T. Pedersen & Ilya Petoukhov & Judith M. Vonk & Ulrike Gehring & Marijn Berg & Marnix Bügel & Orestes A. Carpaij & Erick Forno & Andréanne Morin , 2022. "Nasal DNA methylation at three CpG sites predicts childhood allergic disease," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
- Chen, Jian & Katchova, Ani L. & Zhou, Chenxi, 2021.
"Agricultural loan delinquency prediction using machine learning methods,"
International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 24(5), May.
- Chen, Jian & Katchova, Ani, 2019. "Agricultural Loan Delinquency Prediction Using Machine Learning Methods," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 290745, Agricultural and Applied Economics Association.
- Rummens, Anneleen & Hardyns, Wim, 2021. "The effect of spatiotemporal resolution on predictive policing model performance," International Journal of Forecasting, Elsevier, vol. 37(1), pages 125-133.
- Jinzhou Li & Marloes H. Maathuis, 2021. "GGM knockoff filter: False discovery rate control for Gaussian graphical models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 534-558, July.
- Jie Ding & Vahid Tarokh & Yuhong Yang, 2018. "Model Selection Techniques -- An Overview," Papers 1810.09583, arXiv.org.
- Tutz, Gerhard & Pößnecker, Wolfgang & Uhlmann, Lorenz, 2015. "Variable selection in general multinomial logit models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 207-222.
- Oxana Babecka Kucharcukova & Jan Bruha, 2016. "Nowcasting the Czech Trade Balance," Working Papers 2016/11, Czech National Bank.
- Carstensen, Kai & Heinrich, Markus & Reif, Magnus & Wolters, Maik H., 2020.
"Predicting ordinary and severe recessions with a three-state Markov-switching dynamic factor model,"
International Journal of Forecasting, Elsevier, vol. 36(3), pages 829-850.
- Heinrich, Markus & Carstensen, Kai & Reif, Magnus & Wolters, Maik, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," VfS Annual Conference 2017 (Vienna): Alternative Structures for Money and Banking 168206, Verein für Socialpolitik / German Economic Association.
- Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2017. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model. An Application to the German Business Cycle," CESifo Working Paper Series 6457, CESifo.
- Kai Carstensen & Markus Heinrich & Magnus Reif & Maik H. Wolters, 2019. "Predicting Ordinary and Severe Recessions with a Three-State Markov-Switching Dynamic Factor Model," Jena Economics Research Papers 2019-006, Friedrich-Schiller-University Jena.
- Hou-Tai Chang & Ping-Huai Wang & Wei-Fang Chen & Chen-Ju Lin, 2022. "Risk Assessment of Early Lung Cancer with LDCT and Health Examinations," IJERPH, MDPI, vol. 19(8), pages 1-12, April.
- Margherita Giuzio, 2017. "Genetic algorithm versus classical methods in sparse index tracking," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 243-256, November.
- Nicolaj N. Mühlbach, 2020. "Tree-based Synthetic Control Methods: Consequences of moving the US Embassy," CREATES Research Papers 2020-04, Department of Economics and Business Economics, Aarhus University.
- Wang, Qiao & Zhou, Wei & Cheng, Yonggang & Ma, Gang & Chang, Xiaolin & Miao, Yu & Chen, E, 2018. "Regularized moving least-square method and regularized improved interpolating moving least-square method with nonsingular moment matrices," Applied Mathematics and Computation, Elsevier, vol. 325(C), pages 120-145.
- Dmitriy Drusvyatskiy & Adrian S. Lewis, 2018. "Error Bounds, Quadratic Growth, and Linear Convergence of Proximal Methods," Mathematics of Operations Research, INFORMS, vol. 43(3), pages 919-948, August.
- Mkhadri, Abdallah & Ouhourane, Mohamed, 2013. "An extended variable inclusion and shrinkage algorithm for correlated variables," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 631-644.
- Lucian Belascu & Alexandra Horobet & Georgiana Vrinceanu & Consuela Popescu, 2021. "Performance Dissimilarities in European Union Manufacturing: The Effect of Ownership and Technological Intensity," Sustainability, MDPI, vol. 13(18), pages 1-19, September.
- Candelon, B. & Hurlin, C. & Tokpavi, S., 2012.
"Sampling error and double shrinkage estimation of minimum variance portfolios,"
Journal of Empirical Finance, Elsevier, vol. 19(4), pages 511-527.
- Candelon, B. & Hurlin, C. & Tokpavi, S., 2011. "Sampling error and double shrinkage estimation of minimum variance portfolios," Research Memorandum 002, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
- Bertrand Candelon & Christophe Hurlin & Sessi Tokpavi, 2012. "Sampling Error and Double Shrinkage Estimation of Minimum Variance Portfolios," Post-Print hal-01385835, HAL.
- Susan Athey & Guido W. Imbens & Stefan Wager, 2018.
"Approximate residual balancing: debiased inference of average treatment effects in high dimensions,"
Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(4), pages 597-623, September.
- Susan Athey & Guido W. Imbens & Stefan Wager, 2016. "Approximate Residual Balancing: De-Biased Inference of Average Treatment Effects in High Dimensions," Papers 1604.07125, arXiv.org, revised Jan 2018.
- Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2022. "Specification Choices in Quantile Regression for Empirical Macroeconomics," Working Papers 22-25, Federal Reserve Bank of Cleveland.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0202498. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.