  <record>
    <language>eng</language>
    <publisher>TQMP</publisher>
    <journalTitle>Tutorials in Quantitative Methods for Psychology</journalTitle>
    <issn>1913-4126</issn>
    <publicationDate>2007-09-01</publicationDate>
    <volume>3</volume>
    <issue>2</issue>
    <startPage>51</startPage>
    <endPage>59</endPage>
    <documentType>article</documentType>
    <title language="eng">A short tutorial of GPower</title>

    <authors>
      <author>
        <name>Susanne Mayr</name>
        <email>susanne.mayr@uni-duesseldorf.de</email>
        <affiliationId>1</affiliationId>
      </author>

      <author>
        <name>Edgar Erdfelder</name>
        <email>erdfelder@psychologie.uni-mannheim.de</email>
        <affiliationId>2</affiliationId>
      </author>


      <author>
        <name>Axel Buchner</name>
        <email>axel.buchner@uni-duesseldorf.de</email>
        <affiliationId>1</affiliationId>
      </author>


      <author>
        <name>Franz Faul</name>
        <email>ffaul@psychologie.uni-kiel.de</email>
        <affiliationId>3</affiliationId>
      </author>


    </authors>

    <affiliationsList>
      <affiliationName affiliationId="1">Heinrich-Heine-Universität, Düsseldorf, Germany</affiliationName>

      <affiliationName affiliationId="2">Universität Mannheim, Mannheim, Germany</affiliationName>


      <affiliationName affiliationId="3">Christian-Albrechts-Universität, Kiel, Germany</affiliationName>



    </affiliationsList>

    <abstract language="eng">
       The purpose of this paper is to promote statistical power analysis in the behavioral sciences by introducing the easy to use GPower software. GPower is a free general power analysis program available in two essentially equivalent versions, one designed for Macintosh OS/OS X and the other for MS-DOS/Windows platforms. Psychological research examples are presented to illustrate the various features of the GPower software. In particular, a priori, post-hoc, and compromise power analyses for t-tests, F-tests, and chi-2-tests will be demonstrated. For all examples, the underlying statistical concepts as well as the implementation in GPower will be described.  
    </abstract>

    <fullTextUrl format="pdf">http://www.tqmp.org/Content/vol03-2/p051/p051.pdf</fullTextUrl>

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

      <keyword>statistical power</keyword>




    </keywords>
  </record>


