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backward elimination

backward elimination Backward elimination is a variable-selection method used in regression modeling to decide which predictors to keep in a multivariable analysis.

Backward elimination is a variable-selection method used in regression modeling to decide which predictors to keep in a multivariable analysis. It refers to removing variables from a model so the final model includes a selected set of predictors.

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Sources

Drafting source: Schernhammer Eva S.; Weitzer Jakob; Han Emilie; Bertau Martin; Zenk Lukas; Caniglia Guido; Laubichler Manfred D.; Birmann Brenda M.; Steiner Gerald. Determinants of trust in times of crises: A cross-sectional study of 3,065 German-speaking adults from the D-A-CH region. 2023; DOI 10.1371/journal.pone.0286488; article XML SHA-256 dede7f27bfe5254f56af9897055395db96794632bf7054dcbf2020f414b0f190. “Determinants of trust in times of crises: A cross-sectional study of 3,065 German-speaking adults from the D-A-CH region” (10.1371/journal.pone.0286488).
CC-BY-4.0 · Definition uses new wording; original source retains its stated licence. · Source snapshot SHA-256: dede7f27bfe5254f56af9897055395db96794632bf7054dcbf2020f414b0f190

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PsychTerms (psychterms.org), CC BY 4.0, version 1. “backward elimination.” Development preview.

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