  <record>
    <language>eng</language>
    <publisher>TQMP</publisher>
    <journalTitle>Tutorials in Quantitative Methods for Psychology</journalTitle>
    <issn>1913-4126</issn>
    <publicationDate>2011-04-01</publicationDate>
    <volume>7</volume>
    <issue>1</issue>
    <startPage>15</startPage>
    <endPage>18</endPage>
    <documentType>article</documentType>
    <title language="eng">Randomization test of mean is compuationally inaccessible when the number of groups exceeds two</title>

    <authors>
      <author>
        <name>Denis Cousineau</name>
        <email>denis.cousineau@umontreal.ca</email>
        <affiliationId>1</affiliationId>
      </author>




    </authors>

    <affiliationsList>
      <affiliationName affiliationId="1">Université de Montréal</affiliationName>




    </affiliationsList>

    <abstract language="eng">
       With  the  advent  of  fast  computers,  the  randomization  test  of mean  (also  called  the permutation  test)  received some attention  in  the  recent years. Here we show  that  the 
randomization  test  is  possible  only  for  two-group  design;  comparing  three  groups requires a number of permutations so vast that even three groups of ten participants is beyond the current capabilities of modern computers. Further, we show that the rate of increase  in  the  number  of  permutation  is  so  large  that  simply  adding  one  more participant per group  to  the data  results  in a  computation  time  increased by at  least one  order  of magnitude  (in  the  three-group  design)  or more. Hence,  the  exhaustive randomization test may never be a viable alternative to ANOVAs.  
    </abstract>

    <fullTextUrl format="pdf">http://www.tqmp.org/Content/vol07-1/p015/p015.pdf</fullTextUrl>

    <keywords language="eng">    
      <keyword>Randomization test</keyword>

      <keyword>statistics</keyword>




    </keywords>
  </record>


