  <record>
    <language>eng</language>
    <publisher>TQMP</publisher>
    <journalTitle>Tutorials in Quantitative Methods for Psychology</journalTitle>
    <issn>1913-4126</issn>
    <publicationDate>2008-09-01</publicationDate>
    <volume>4</volume>
    <issue>2</issue>
    <startPage>65</startPage>
    <endPage>78</endPage>
    <documentType>article</documentType>
    <title language="eng">General Linear Models: An Integrated Approach to Statistics</title>

    <authors>
      <author>
        <name>Sylvain Chartier</name>
        <email>sylvain.chartier@uottawa.ca</email>
        <affiliationId>1</affiliationId>
      </author>

      <author>
        <name>Andrew Faulkner</name>
        <email>af@uottawa.ca</email>
        <affiliationId>1</affiliationId>
      </author>




    </authors>

    <affiliationsList>
      <affiliationName affiliationId="1">University of Ottawa</affiliationName>




    </affiliationsList>

    <abstract language="eng">
       Generally, in psychology, the various statistical analyses are taught independently from each other. As a consequence, students struggle to learn new statistical analyses, in contexts that differ from their textbooks. This paper gives a short introduction to the general linear model (GLM), in which it is showed that ANOVA (one-way, factorial, repeated measure and analysis of covariance) is simply a multiple correlation/regression analysis (MCRA). Generalizations to other cases, such as multivariate and nonlinear analysis, are also discussed.  It can easily be shown that every popular linear analysis can be derived from understanding MCRA.  
    </abstract>

    <fullTextUrl format="pdf">http://www.tqmp.org/Content/vol04-2/p065/p065.pdf</fullTextUrl>

    <keywords language="eng">    
      <keyword>Stastitics</keyword>

      <keyword>General linear model</keyword>




    </keywords>
  </record>


