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collinearity

collinearity Collinearity is a situation in which measured variables are so strongly related that their unique associations become hard to separate in a statistical model.

Collinearity is a situation in which measured variables are so strongly related that their unique associations become hard to separate in a statistical model. In this study context, high collinearity was taken as a sign of possible construct overlap and a reason to interpret unexpected coefficients cautiously.

Sources

Drafting source: Li Junfei; Huang Jinyan; Kumar Jai. Community of inquiry presences and undergraduates’ online learning outcomes: self-regulated learning as a pathway and knowledge-seeking intention as a boundary condition. 2026; DOI 10.3389/fpsyg.2026.1895876; article XML SHA-256 66d2fa49c4c0d13211d137ce4b57618a3c43d190a8d4a06bff23ec80e6731278. “Community of inquiry presences and undergraduates’ online learning outcomes: self-regulated learning as a pathway and knowledge-seeking intention as a boundary condition” (10.3389/fpsyg.2026.1895876).
CC-BY-4.0 · Definition uses new wording; original source retains its stated licence. · Source snapshot SHA-256: 66d2fa49c4c0d13211d137ce4b57618a3c43d190a8d4a06bff23ec80e6731278

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PsychTerms (psychterms.org), CC BY 4.0, version 2. “collinearity.” Development preview.

Version 2 · SHA-256: 3b0b5d90b9ed223b361f38ac899788ce82df7205cc95604595d67a9900cfe1ce

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collinearity

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Sources

Cite this entry