Multiple Linear Regression Applications and Multicollinearity: A Bibliometric Analysis

Maricela Fernanda Ormaza Morejon; Rolando Ismael Yépez Moreira; Edison Noe Buenaño Buenaño; Juan Carlos Muyulema Allaica

doi:10.1007/978-981-97-9324-2_29

Multiple Linear Regression Applications and Multicollinearity: A Bibliometric Analysis

Maricela Fernanda Ormaza Morejon^*
, Rolando Ismael Yépez Moreira
, Edison Noe Buenaño Buenaño
, Juan Carlos Muyulema Allaica

^*Autor correspondiente de este trabajo

PUCE Ibarra

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

Resumen

The bibliometric study addresses the scientific production employing multiple linear regression (MLR) and multicollinearity management for predictive model generation. It analyzes 541 articles from 1982 to 2023, highlighting steady annual growth and geographical distribution of research. The United States and China lead production, comprising 36.86% of documents. A growing trend in linear regression use within machine learning is observed. Applied research tackles multidisciplinary issues, primarily in social sciences. This study provides a detailed overview of current status, trends, and contributions in multicollinearity management in MLR models, emphasizing the importance of addressing this challenge for stable and valid predictive models.

Idioma original	Inglés
Título de la publicación alojada	Intelligent Sustainable Systems - Selected Papers of WorldS4 2024
Editores	Atulya Nagar, Dharm Singh Jat, Durgesh Mishra, Amit Joshi
Editorial	Springer Science and Business Media Deutschland GmbH
Páginas	355-371
Número de páginas	17
ISBN (versión impresa)	9789819793235
DOI	https://doi.org/10.1007/978-981-97-9324-2_29
Estado	Publicada - 2025
Evento	8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024 - London, Reino Unido Duración: 23 jul. 2024 → 26 jul. 2024

Serie de la publicación

Nombre	Lecture Notes in Networks and Systems
Volumen	1180 LNNS
ISSN (versión impresa)	2367-3370
ISSN (versión digital)	2367-3389

Conferencia

Conferencia	8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024
País/Territorio	Reino Unido
Ciudad	London
Período	23/07/24 → 26/07/24

Nota bibliográfica

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

Acceder al documento

10.1007/978-981-97-9324-2_29

Otros archivos y enlaces

Enlace a la publicación en Scopus

Citar esto

Morejon, M. F. O., Moreira, R. I. Y., Buenaño, E. N. B., & Allaica, J. C. M. (2025). Multiple Linear Regression Applications and Multicollinearity: A Bibliometric Analysis. En A. Nagar, D. S. Jat, D. Mishra, & A. Joshi (Eds.), Intelligent Sustainable Systems - Selected Papers of WorldS4 2024 (pp. 355-371). (Lecture Notes in Networks and Systems; Vol. 1180 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-9324-2_29

Morejon, Maricela Fernanda Ormaza ; Moreira, Rolando Ismael Yépez ; Buenaño, Edison Noe Buenaño et al. / Multiple Linear Regression Applications and Multicollinearity : A Bibliometric Analysis. Intelligent Sustainable Systems - Selected Papers of WorldS4 2024. editor / Atulya Nagar ; Dharm Singh Jat ; Durgesh Mishra ; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2025. pp. 355-371 (Lecture Notes in Networks and Systems).

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title = "Multiple Linear Regression Applications and Multicollinearity: A Bibliometric Analysis",

abstract = "The bibliometric study addresses the scientific production employing multiple linear regression (MLR) and multicollinearity management for predictive model generation. It analyzes 541 articles from 1982 to 2023, highlighting steady annual growth and geographical distribution of research. The United States and China lead production, comprising 36.86\% of documents. A growing trend in linear regression use within machine learning is observed. Applied research tackles multidisciplinary issues, primarily in social sciences. This study provides a detailed overview of current status, trends, and contributions in multicollinearity management in MLR models, emphasizing the importance of addressing this challenge for stable and valid predictive models.",

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note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.; 8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024 ; Conference date: 23-07-2024 Through 26-07-2024",

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doi = "10.1007/978-981-97-9324-2\_29",

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Morejon, MFO, Moreira, RIY, Buenaño, ENB & Allaica, JCM 2025, Multiple Linear Regression Applications and Multicollinearity: A Bibliometric Analysis. En A Nagar, DS Jat, D Mishra & A Joshi (eds.), Intelligent Sustainable Systems - Selected Papers of WorldS4 2024. Lecture Notes in Networks and Systems, vol. 1180 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 355-371, 8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024, London, Reino Unido, 23/07/24. https://doi.org/10.1007/978-981-97-9324-2_29

Multiple Linear Regression Applications and Multicollinearity: A Bibliometric Analysis. / Morejon, Maricela Fernanda Ormaza; Moreira, Rolando Ismael Yépez; Buenaño, Edison Noe Buenaño et al.
Intelligent Sustainable Systems - Selected Papers of WorldS4 2024. ed. / Atulya Nagar; Dharm Singh Jat; Durgesh Mishra; Amit Joshi. Springer Science and Business Media Deutschland GmbH, 2025. p. 355-371 (Lecture Notes in Networks and Systems; Vol. 1180 LNNS).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución de conferencia › revisión exhaustiva

TY - GEN

T1 - Multiple Linear Regression Applications and Multicollinearity

T2 - 8th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2024

AU - Morejon, Maricela Fernanda Ormaza

AU - Moreira, Rolando Ismael Yépez

AU - Buenaño, Edison Noe Buenaño

AU - Allaica, Juan Carlos Muyulema

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

PY - 2025

Y1 - 2025

N2 - The bibliometric study addresses the scientific production employing multiple linear regression (MLR) and multicollinearity management for predictive model generation. It analyzes 541 articles from 1982 to 2023, highlighting steady annual growth and geographical distribution of research. The United States and China lead production, comprising 36.86% of documents. A growing trend in linear regression use within machine learning is observed. Applied research tackles multidisciplinary issues, primarily in social sciences. This study provides a detailed overview of current status, trends, and contributions in multicollinearity management in MLR models, emphasizing the importance of addressing this challenge for stable and valid predictive models.

AB - The bibliometric study addresses the scientific production employing multiple linear regression (MLR) and multicollinearity management for predictive model generation. It analyzes 541 articles from 1982 to 2023, highlighting steady annual growth and geographical distribution of research. The United States and China lead production, comprising 36.86% of documents. A growing trend in linear regression use within machine learning is observed. Applied research tackles multidisciplinary issues, primarily in social sciences. This study provides a detailed overview of current status, trends, and contributions in multicollinearity management in MLR models, emphasizing the importance of addressing this challenge for stable and valid predictive models.

KW - Machine learning

KW - Multicollinearity

KW - Multiple linear regression (MLR)

KW - Predictive models

KW - Scientific production

UR - https://www.scopus.com/pages/publications/105016201432

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DO - 10.1007/978-981-97-9324-2_29

M3 - Conference contribution

AN - SCOPUS:105016201432

SN - 9789819793235

T3 - Lecture Notes in Networks and Systems

SP - 355

EP - 371

BT - Intelligent Sustainable Systems - Selected Papers of WorldS4 2024

A2 - Nagar, Atulya

A2 - Jat, Dharm Singh

A2 - Mishra, Durgesh

A2 - Joshi, Amit

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 23 July 2024 through 26 July 2024

ER -

Morejon MFO, Moreira RIY, Buenaño ENB, Allaica JCM. Multiple Linear Regression Applications and Multicollinearity: A Bibliometric Analysis. En Nagar A, Jat DS, Mishra D, Joshi A, editores, Intelligent Sustainable Systems - Selected Papers of WorldS4 2024. Springer Science and Business Media Deutschland GmbH. 2025. p. 355-371. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-97-9324-2_29