Variable selection strategies and its importance in clinical prediction modelling
Datos Bibliográficos
| ID | 23382525 |
|---|---|
| Autores | Mohammad Ziaul Islam Chowdhury (University of Calgary), Tanvir Chowdhury Turin (0000-0002-7499-5050, University of Calgary, autor de correspondencia) |
| Año | 2020 |
| Volumen | 8 |
| Número | 1 |
| Páginas | e000262 |
| Fecha de publicación | 2020-02-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Family Medicine and Community Health (JOURNAL) |
| Identificadores de la revista | ISSN: 2305-6983 • E-ISSN: 2009-8774 |
| Editorial | BMJ (PUBLISHER • GB) |
| DOI | 10.1136/fmch-2019-000262 |
| PMID | 32148735 |
| OpenAlex | W3008867523 |
| Idioma | EN |
| Citas recibidas | 86 |
| Referencias citadas | 26 |
Clinical prediction models are used frequently in clinical practice to identify patients who are at risk of developing an adverse outcome so that preventive measures can be initiated. A prediction model can be developed in a number of ways; however, an appropriate variable selection strategy needs to be followed in all cases. Our purpose is to introduce readers to the concept of variable selection in prediction modelling, including the importance of variable selection and variable reduction strategies. We will discuss the various variable selection techniques that can be applied during prediction model building (backward elimination, forward selection, stepwise selection and all possible subset selection), and the stopping rule/selection criteria in variable selection (p values, Akaike information criterion, Bayesian information criterion and Mallows’ C p statistic). This paper focuses on the importance of including appropriate variables, following the proper steps, and adopting the proper methods when selecting variables for prediction models.
Akaike information criterion · Bayesian information criterion · Bayesian probability · Feature selection · Machine learning · Model selection · Selection (genetic algorithm) · Statistic · Statistics · Variable (mathematics) · Artificial Intelligence · Computer Science · Health Systems, Economic Evaluations, Quality of Life · Mathematics · Meta-analysis and systematic reviews · Statistical Methods in Clinical Trials
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| Obras citantes distintas | 86 |
|---|---|
| Citas por año | 17,2 |
| Intervalo de citas | 2021 - 2026 (6) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 76 |