
BOX COX LINEARITY PLOTName:
is essentially the powertransformation family (adjusted to include log transformations). The horizontal axis is the lambda parameter. The vertical axis is the computed correlation coefficient between <y> and the transformed <x> The lambda corresponding to the highest correlation is the appropriate transformation to use in linearizing the relationship between <y> and <x>
<SUBSET/EXCEPT/FOR qualification> where <y> is the first response variable; <x> is the second response variable; and where the <SUBSET/EXCEPT/FOR qualification> is optional.
<SUBSET/EXCEPT/FOR qualification> where <y> is the first response variable; <x> is the second response variable; <tag1> is a groupid variable; and where the <SUBSET/EXCEPT/FOR qualification> is optional. A BoxCox linearity plot will be generated for each distinct value of the groupid variable. These plots will be overlaid on the same plot.
<SUBSET/EXCEPT/FOR qualification> where <y> is the first response variable; <x> is the second response variable; <tag1> is a groupid variable; <tag2> is a groupid variable; and where the <SUBSET/EXCEPT/FOR qualification> is optional. The two groupid variables are crosstabulated and a BoxCox linearity plot will be generated for each distinct combination of values for the groupid variables. These plots will be overlaid on the same plot.
REPLICATED BOXCOX LINEARITY PLOT Y X TAG
NIST/SEMATECH eHandbook of Statistical Methods, BoxCox Linearity Plot, 6/2003. NIST/SEMATECH eHandbook of Statistical Methods, BoxCox Linearity Plot Used in a Case Study, 6/2003.
2010/5: Support for REPLICATION option SKIP 25 READ BERGER1.DAT Y X LABEL CASE ASIS Y1LABEL Correlation X1LABEL Lambda BOX COX LINEARITY PLOT Y XProgram 2: title case asis title offset 2 title automatic label case asis multiplot corner coordinates 0 0 100 95 tic mark offset units screen y1tic mark offset 2 0 . reset data skip 25 read nelson.dat y x tag . replicated box cox linearity plot y x tag  
Date created: 11/30/2010 Last updated: 12/04/2023 Please email comments on this WWW page to alan.heckert@nist.gov. 