Essec\Faculty\Model\Contribution {#6196
  #_index: "academ_contributions"
  #_id: "5322"
  #_source: array:26 [
    "id" => "5322"
    "slug" => "a-partial-least-squares-comprehensive-environment"
    "yearMonth" => "2008-09"
    "year" => "2008"
    "title" => "A Partial Least Squares Comprehensive Environment:"
    "description" => "ESPOSITO VINZI, V. (2008). A Partial Least Squares Comprehensive Environment: Dans: 7th International Conference on Social Science Methodology, RC33 - Logic and Methodology in Sociology."
    "authors" => array:1 [
      0 => array:3 [
        "name" => "ESPOSITO VINZI Vincenzo"
        "bid" => "B00067049"
        "slug" => "esposito-vinzi-vincenzo"
      ]
    ]
    "ouvrage" => "7th International Conference on Social Science Methodology, RC33 - Logic and Methodology in Sociology"
    "keywords" => array:1 [
      0 => "Multicollinearity"
    ]
    "updatedAt" => "2021-04-19 17:57:25"
    "publicationUrl" => null
    "publicationInfo" => array:3 [
      "pages" => null
      "volume" => null
      "number" => null
    ]
    "type" => array:2 [
      "fr" => "Communications dans une conférence"
      "en" => "Presentations at an Academic or Professional conference"
    ]
    "support_type" => array:2 [
      "fr" => null
      "en" => null
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "PLS Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation modelling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships between manifest and latent variables, PLS-PM implies multiple OLS regressions. They might yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables nor in case of missing data. We explore PLS regression (PLS-R) as an external estimation mode to overcome the mentioned problems while preserving formative relationships and being coherent with the component-based and prediction-oriented nature of PLS-PM. PLS-R is also fruitfully extended to the path weighting internal estimation scheme and the estimation of path coefficients."
      "en" => "PLS Path Modelling (PLS-PM) is generally meant as a component-based approach to structural equation modelling that privileges a prediction oriented discovery process to the statistical testing of causal hypotheses. In case of formative relationships between manifest and latent variables, PLS-PM implies multiple OLS regressions. They might yield unstable results in case of strong correlations between manifest variables while being not feasible when the number of observations is smaller than the number of variables nor in case of missing data. We explore PLS regression (PLS-R) as an external estimation mode to overcome the mentioned problems while preserving formative relationships and being coherent with the component-based and prediction-oriented nature of PLS-PM. PLS-R is also fruitfully extended to the path weighting internal estimation scheme and the estimation of path coefficients."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d’Information, Sciences de la Décision et Statistiques"
      "en" => "Information Systems, Decision Sciences and Statistics"
    ]
    "indexedAt" => "2024-04-16T19:22:01.000Z"
    "docTitle" => "A Partial Least Squares Comprehensive Environment:"
    "docSurtitle" => "Communications dans une conférence"
    "authorNames" => "<a href="/cv/esposito-vinzi-vincenzo">ESPOSITO VINZI Vincenzo</a>"
    "docDescription" => "<span class="document-property-authors">ESPOSITO VINZI Vincenzo</span><br><span class="document-property-authors_fields">Systèmes d’Information, Sciences de la Décision et Statistiques</span> | <span class="document-property-year">2008</span>"
    "keywordList" => "<a href="#">Multicollinearity</a>"
    "docPreview" => "<b>A Partial Least Squares Comprehensive Environment:</b><br><span>2008-09 | Communications dans une conférence </span>"
    "docType" => "research"
    "publicationLink" => "<a href="#" target="_blank">A Partial Least Squares Comprehensive Environment:</a>"
  ]
  +lang: "fr"
  +"_type": "_doc"
  +"_score": 9.153981
  +"parent": null
}