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Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review

The validity of inferences drawn from statistical test results depends on how well data meet associated assumptions. Yet, research (e.g., Hoekstra et al., 2012) indicates that such assumptions are rarely reported in literature and that some researchers might be unfamiliar with the techniques and rem...

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Detalles Bibliográficos
Autor principal: Nimon, Kim F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Research Foundation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3428812/
https://www.ncbi.nlm.nih.gov/pubmed/22973253
http://dx.doi.org/10.3389/fpsyg.2012.00322
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author Nimon, Kim F.
author_facet Nimon, Kim F.
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description The validity of inferences drawn from statistical test results depends on how well data meet associated assumptions. Yet, research (e.g., Hoekstra et al., 2012) indicates that such assumptions are rarely reported in literature and that some researchers might be unfamiliar with the techniques and remedies that are pertinent to the statistical tests they conduct. This article seeks to support researchers by concisely reviewing key statistical assumptions associated with substantive statistical tests across the general linear model. Additionally, the article reviews techniques to check for statistical assumptions and identifies remedies and problems if data do not meet the necessary assumptions.
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spelling pubmed-34288122012-09-12 Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review Nimon, Kim F. Front Psychol Psychology The validity of inferences drawn from statistical test results depends on how well data meet associated assumptions. Yet, research (e.g., Hoekstra et al., 2012) indicates that such assumptions are rarely reported in literature and that some researchers might be unfamiliar with the techniques and remedies that are pertinent to the statistical tests they conduct. This article seeks to support researchers by concisely reviewing key statistical assumptions associated with substantive statistical tests across the general linear model. Additionally, the article reviews techniques to check for statistical assumptions and identifies remedies and problems if data do not meet the necessary assumptions. Frontiers Research Foundation 2012-08-28 /pmc/articles/PMC3428812/ /pubmed/22973253 http://dx.doi.org/10.3389/fpsyg.2012.00322 Text en Copyright © 2012 Nimon. http://www.frontiersin.org/licenseagreement This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
spellingShingle Psychology
Nimon, Kim F.
Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review
title Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review
title_full Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review
title_fullStr Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review
title_full_unstemmed Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review
title_short Statistical Assumptions of Substantive Analyses Across the General Linear Model: A Mini-Review
title_sort statistical assumptions of substantive analyses across the general linear model: a mini-review
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3428812/
https://www.ncbi.nlm.nih.gov/pubmed/22973253
http://dx.doi.org/10.3389/fpsyg.2012.00322
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