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

Artificial Intelligence (1371) Machine Learning (1465) Clinical Information and Decision Making (1407)

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 (4) 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
  3. Tan A, Ali F, Poon K. Subjective well‐being of children with special educational needs: Longitudinal predictors using machine learning. Applied Psychology: Health and Well-Being 2024 View

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