RT Book, Section
A1 Glantz, Stanton A.
SR Print(0)
ID 57417951
T1 Chapter 10. Alternatives to Analysis of Variance and the t Test Based on Ranks
T2 Primer of Biostatistics, 7e
YR 2012
FD 2012
PB The McGraw-Hill Companies
PP New York, NY
SN 978-0-07-178150-3
LK accessanesthesiology.mhmedical.com/content.aspx?aid=57417951
RD 2024/04/19
AB Analysis  of  variance,  including  the  t  tests,  is  widely  used  to  test  the  hypothesis  that  one  or  more  treatments  had  no  effect  on  the  mean  of  some  observed  variable.  All  forms  of  analysis  of  variance,  including  the  t  tests,  are  based  on  the  assumption  that  the  observations  are  drawn  from  normally  distributed  populations  in  which  the  variances  are  the  same  even  if  the  treatments  change  the  mean  responses.  These  assumptions  are  often  satisfied  well  enough  to  make  analysis  of  variance  an  extremely  useful  statistical  procedure.  On  the  other  hand,  experiments  often  yield  data  that  are  not  compatible  with  these  assumptions.  In  addition,  there  are  often  problems  in  which  the  observations  are  measured  on  an  ordinal  scale  rather  than  an  interval  scale  and  may  not  be  amenable  to  an  analysis  of  variance.  This  chapter  develops  analogs  to  the  t  tests  and  analysis  of  variance  based  on  ranks  of  the  observations  rather  than  the  observations  themselves.  This  approach  uses  information  about  the  relative  sizes  of  the  observations  without  assuming  anything  about  the  specific  nature  of  the  population  they  were  drawn  from.