This paper is in the following e-collection/theme issue:

Artificial Intelligence (2129) Machine Learning (2076) Clinical Information and Decision Making (1915)

Published on in Vol 23, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/22021, first published .
Relative Performance of Machine Learning and Linear Regression in Predicting Quality of Life and Academic Performance of School Children in Norway: Data Analysis of a Quasi-Experimental Study

Relative Performance of Machine Learning and Linear Regression in Predicting Quality of Life and Academic Performance of School Children in Norway: Data Analysis of a Quasi-Experimental Study

Relative Performance of Machine Learning and Linear Regression in Predicting Quality of Life and Academic Performance of School Children in Norway: Data Analysis of a Quasi-Experimental Study

Authors of this article:

Robert Froud1, 2 Author Orcid Image ;   Solveig Hakestad Hansen1 Author Orcid Image ;   Hans Kristian Ruud1 Author Orcid Image ;   Jonathan Foss3 Author Orcid Image ;   Leila Ferguson1 Author Orcid Image ;   Per Morten Fredriksen1 Author Orcid Image
Article Authors Cited by (10) Tweetations (6) Metrics

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  2. González-Carrasco M, Aciar S, Casas F, Oriol X, Fabregat R, Malo S. A Machine Learning Approach to Well-Being in Late Childhood and Early Adolescence: The Children’s Worlds Data Case. Social Indicators Research 2024;175(1):25 View
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  4. Bouliotis G, Underwood M, Froud R. Predicting the time to get back to work using statistical models and machine learning approaches. BMC Medical Research Methodology 2024;24(1) View
  5. Khine M, Liu Y, Pallipuram V, Afari E. A Machine-Learning Approach to Predicting the Achievement of Australian Students Using School Climate; Learner Characteristics; and Economic, Social, and Cultural Status. Education Sciences 2024;14(12):1350 View
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  7. Winn K, Chen G, Woode M. Exploring the Complexity of the Relationship between Global Life Satisfaction and Satisfaction with Life Domains in Early Adolescents. Child Indicators Research 2025;18(6):2677 View
  8. Das P, Arif M, Hasan M, ALmerab M, Habib A, Al Mamun F, Mamun M, Gozal D. Prevalence and Factors Associated with Insomnia Among Chronic Disease Patients in Bangladesh: A Machine Learning Study. Nature and Science of Sleep 2025;Volume 17:2541 View

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  1. Espinosa-Pinos C, Ayala-Chauvín I, Buele J. Technologies and Innovation. View
  2. Valenzuela Hernández J, Mora Castro G, Bojórquez Delgado G. Investigaciones actuales de la computación. View