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Biplot

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akbreezo View Drop Down
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Joined: 13 Apr 2010
Location: United States
Online Status: Offline
Posts: 1
  Quote akbreezo Quote  Post ReplyReply bullet Topic: Biplot
    Posted: 13 Apr 2010 at 11:02pm
I'm looking for produce a biplot for stable isotope data. I need to plot means with standard errors of two variables. I had syntax that would product this plot in SPSS 14.0, but I have upgraded to PASW 18 and the syntax no longer works.
I have posted the syntax below.
Thanks all!
Bree

GGRAPH
/GRAPHDATASET NAME="FeedingForCharts" VARIABLES=MEANSE(d13C, 1)[NAME="MEAN_d13C"
LOW="MEAN_d13C_LOW" HIGH="MEAN_d13C_HIGH"]
MEANSE(d15N, 1)[NAME="MEAN_d15N" LOW="MEAN_d15N_LOW"
HIGH="MEAN_d15N_HIGH"]
group MISSING=LISTWISE REPORTMISSING=NO
/GRAPHSPEC SOURCE=INLINE.
BEGIN GPL
SOURCE: s=userSource(id("FeedingForCharts"))
DATA: MEAN_d13C=col(source(s), name("MEAN_d13C"))
DATA: LOW_d13C=col(source(s), name("MEAN_d13C_LOW"))
DATA: HIGH_d13C=col(source(s), name("MEAN_d13C_HIGH"))
DATA: MEAN_d15N=col(source(s), name("MEAN_d15N"))
DATA: LOW_d15N=col(source(s), name("MEAN_d15N_LOW"))
DATA: HIGH_d15N=col(source(s), name("MEAN_d15N_HIGH"))
DATA: group=col(source(s), name("group"), unit.category())
GUIDE: axis(dim(1), label("d13C"))
GUIDE: axis(dim(2), label("d15N"))
GUIDE: legend(aesthetic(aesthetic.color.interior), null())
ELEMENT: point(position(MEAN_d13C*MEAN_d15N), color(group))
ELEMENT: line(position(MEAN_d13C*(LOW_d15N+HIGH_d15N)),color(group))
ELEMENT: line(position((LOW_d13C+HIGH_d13C)*MEAN_d15N)),color(group))
END GPL.
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stats13 View Drop Down
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Joined: 13 Nov 2009
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Posts: 17
  Quote stats13 Quote  Post ReplyReply bullet Posted: 20 Apr 2010 at 3:41pm

Kindly look at the syntax below where I have plotted means with standard error of 2 variables

DATASET ACTIVATE DataSet2.
* Chart Builder.
GGRAPH
  /GRAPHDATASET NAME="graphdataset" VARIABLES=gender MEANSE(salary, 2)[name="MEAN_salary"
    LOW="MEAN_salary_LOW" HIGH="MEAN_salary_HIGH"] MISSING=LISTWISE REPORTMISSING=NO
  /GRAPHSPEC SOURCE=INLINE.
BEGIN GPL
  SOURCE: s=userSource(id("graphdataset"))
  DATA: gender=col(source(s), name("gender"), unit.category())
  DATA: MEAN_salary=col(source(s), name("MEAN_salary"))
  DATA: LOW=col(source(s), name("MEAN_salary_LOW"))
  DATA: HIGH=col(source(s), name("MEAN_salary_HIGH"))
  GUIDE: axis(dim(1), label("Gender"))
  GUIDE: axis(dim(2), label("Mean Current Salary"))
  GUIDE: text.footnote(label("Error Bars: +/- 2 SE"))
  SCALE: cat(dim(1), include("f", "m"))
  SCALE: linear(dim(2), include(0))
  ELEMENT: interval(position(gender*MEAN_salary), shape.interior(shape.square))
  ELEMENT: interval(position(region.spread.range(gender*(LOW+HIGH))), shape.interior(shape.ibeam))
END GPL.

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