@prefix n9j: <http://data.loterre.fr/ark:/67375/N9J> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .
@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix isothes: <http://purl.org/iso25964/skos-thes#> .

n9j:-M80QV1CJ-G
  owl:sameAs <https://concepts.sagepub.com/social-science/concept/collinearity> ;
  skos:definition "Collinearity is a situation in which the predictor, or exogenous, variables in a linear regression model are linearly related among themselves or with the intercept term, and this relation may lead to adverse effects on the estimated model parameters, particularly the regression coefficients and their associated standard errors. In practice, researchers often treat correlation between predictor variables as collinearity, but strictly speaking they are not the same; strong correlation implies collinearity, but the opposite is not necessarily true. [Source: Encyclopedia of Research Design; Collinearity]"@en ;
  a skos:Concept ;
  skos:inScheme n9j: ;
  skos:broader n9j:-C8NQZ4GL-J ;
  skos:prefLabel "collinearity"@en .

n9j:-methods
  a isothes:ConceptGroup ;
  skos:prefLabel "methods"@en ;
  skos:member n9j:-M80QV1CJ-G .

n9j:-C8NQZ4GL-J
  skos:prefLabel "statistics and research methods"@en ;
  a skos:Concept ;
  skos:narrower n9j:-M80QV1CJ-G .

n9j: a skos:ConceptScheme .