UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

State of the art in selection of variables and functional forms in multivariable analysis-outstanding issues

Sauerbrei, W; Perperoglou, A; Schmid, M; Abrahamowicz, M; Becher, H; Binder, H; Dunkler, D; ... for TG2 of the STRATOS initiative; + view all (2020) State of the art in selection of variables and functional forms in multivariable analysis-outstanding issues. Diagnostic and Prognostic Research , 4 , Article 3. 10.1186/s41512-020-00074-3. Green open access

[thumbnail of State of the art in selection of variables and functional forms in multivariable analysis-outstanding issues.pdf]
Preview
Text
State of the art in selection of variables and functional forms in multivariable analysis-outstanding issues.pdf - Accepted Version

Download (734kB) | Preview

Abstract

Background: How to select variables and identify functional forms for continuous variables is a key concern when creating a multivariable model. Ad hoc ‘traditional’ approaches to variable selection have been in use for at least 50 years. Similarly, methods for determining functional forms for continuous variables were first suggested many years ago. More recently, many alternative approaches to address these two challenges have been proposed, but knowledge of their properties and meaningful comparisons between them are scarce. To define a state of the art and to provide evidence-supported guidance to researchers who have only a basic level of statistical knowledge, many outstanding issues in multivariable modelling remain. Our main aims are to identify and illustrate such gaps in the literature and present them at a moderate technical level to the wide community of practitioners, researchers and students of statistics. Methods: We briefly discuss general issues in building descriptive regression models, strategies for variable selection, different ways of choosing functional forms for continuous variables and methods for combining the selection of variables and functions. We discuss two examples, taken from the medical literature, to illustrate problems in the practice of modelling. Results: Our overview revealed that there is not yet enough evidence on which to base recommendations for the selection of variables and functional forms in multivariable analysis. Such evidence may come from comparisons between alternative methods. In particular, we highlight seven important topics that require further investigation and make suggestions for the direction of further research. Conclusions: Selection of variables and of functional forms are important topics in multivariable analysis. To define a state of the art and to provide evidence-supported guidance to researchers who have only a basic level of statistical knowledge, further comparative research is required.

Type: Article
Title: State of the art in selection of variables and functional forms in multivariable analysis-outstanding issues
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1186/s41512-020-00074-3
Publisher version: https://doi.org/10.1186/s41512-020-00074-3
Language: English
Additional information: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords: Descriptive modelling, Methods for variable selection, Spline procedures, Fractional polynomials, Categorisation, Bias, Shrinkage, Empirical evidence, STRATOS initiative
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Inst of Clinical Trials and Methodology > MRC Clinical Trials Unit at UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10095418
Downloads since deposit
41Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item