ArticlePloS one2014
Augmented backward elimination: a pragmatic and purposeful way to develop statistical models.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers, 1 of them a synthesis that pooled it.
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Who cites it
79 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Associations between Food Group Intake, Cognition, and Academic Achievement in Elementary Schoolchildren.Nutrients · 2019Trial
- Polysomnographic Endotyping to Select Patients with Obstructive Sleep Apnea for Oral Appliances.Annals of the American Thoracic Society · 2019Trial
- Long-Term Trajectories of Multidimensional Outcomes in Psychosis Following Early Intervention During the Critical Period: The PEPP-Montreal 10+ Study Protocol.Early intervention in psychiatry · 2026Article
- Predicting mortality risk in hospitalized ACS patients with hypertensive comorbidity: an interpretable machine learning approach.BMC medical informatics and decision making · 2026Article
- Identifying Long Covid phenotypes and their association with personal characteristics, healthcare use, and daily life burden: population-based study in Belgium.Scientific reports · 2026Article
- Profiles of Risky Sexual Behaviors and Associated Factors Among Sexually Active Men in Rwanda: A Nationwide Survey.Archives of sexual behavior · 2026Article
- Therapeutic Strategies After Discontinuation of Valproate By Females with Epilepsy of Child-Bearing Potential: An Insurance Claims Database Study in France and the United Kingdom.Clinical drug investigation · 2026Article
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- Determinants of overweight and obesity and other cardiometabolic risks in adolescents: a Spanish longitudinal birth study.Pediatric research · 2025Article
- Treatment Outcomes With an Oral Short Course Regimen for Rifampicin-resistant Tuberculosis in a High HIV Prevalence, Programmatic Setting in South Africa.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2025Article
- Protocol for an observational prospective study on the use and impact of over-the-phone interpretation in 911 calls with language discordance.BMC public health · 2025Observational
- Deposition of Mesoporous Silicon Dioxide Films Using Microwave PECVD.Materials (Basel, Switzerland) · 2025Article
- Segregation of three resting-state brain networks predicts reappraisal success across the lifespan.Social cognitive and affective neuroscience · 2025Article
- The edge orientation entropy of natural scenes is associated with infant visual preferences and adult aesthetic judgements.PloS one · 2025Article
- Modifications of the Effect of Juvenile Idiopathic Arthritis (JIA) on Anxiety and Depression in Children and Adolescents: A Pseudo-longitudinal Study of 192,019 Children in the United States.Clinical practice and epidemiology in mental health : CP & EMH · 2025Article
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- Risk and protective factors for suicidal thoughts and behaviors among Black female and male youth with depression symptoms - United States, 2004-2019.Journal of affective disorders · 2024Article
19 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Statistical models are simple mathematical rules derived from empirical data describing the association between an outcome and several explanatory variables. In a typical modeling situation statistical analysis often involves a large number of potential explanatory variables and frequently only partial subject-matter knowledge is available. Therefore, selecting the most suitable variables for a model in an objective and practical manner is usually a non-trivial task. We briefly revisit the purposeful variable selection procedure suggested by Hosmer and Lemeshow which combines significance and change-in-estimate criteria for variable selection and critically discuss the change-in-estimate criterion. We show that using a significance-based threshold for the change-in-estimate criterion reduces to a simple significance-based selection of variables, as if the change-in-estimate criterion is not considered at all. Various extensions to the purposeful variable selection procedure are suggested. We propose to use backward elimination augmented with a standardized change-in-estimate criterion on the quantity of interest usually reported and interpreted in a model for variable selection. Augmented backward elimination has been implemented in a SAS macro for linear, logistic and Cox proportional hazards regression. The algorithm and its implementation were evaluated by means of a simulation study. Augmented backward elimination tends to select larger models than backward elimination and approximates the unselected model up to negligible differences in point estimates of the regression coefficients. On average, regression coefficients obtained after applying augmented backward elimination were less biased relative to the coefficients of correctly specified models than after backward elimination. In summary, we propose augmented backward elimination as a reproducible variable selection algorithm that gives the analyst more flexibility in adopting model selection to a specific statistical modeling situation.
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