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Date:         Sun, 15 Jun 2008 17:01:09 -0500
Reply-To:     "data _null_," <datanull@GMAIL.COM>
Sender:       "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From:         "data _null_," <datanull@GMAIL.COM>
Subject:      Re: Means table using Proc Report
Comments: To: jiana <u44208@uwe.uga.edu>
In-Reply-To:  <7367b4e20806140624y3ff72165p62984905a7f48b2c@mail.gmail.com>
Content-Type: text/plain; charset=ISO-8859-1

I like this a little better. I believe it is more similar to the OPs original need.

title 'Balanced Data from Randomized Complete Block'; data plants; input Type $ @; do Block = 1 to 3; input StemLength @; Stem2 = StemLength+rannor(12345)*4.1; Stem3 = StemLength+rannor(12335)*.4; output; end; datalines; Clarion 32.7 32.3 31.5 Clinton 32.1 29.7 29.1 Knox 35.7 35.9 33.1 O'Neill 36.0 34.2 31.2 Compost 31.8 28.0 29.2 Wabash 38.2 37.8 31.9 Webster 32.5 31.1 29.7 ;;;; run;

ods output mclines=mclines; proc glm order=data; class Block Type; model Stem: = Block Type / solution; means Type / waller regwq; run; quit; data work.mclines2; set work.mclines(where=(mean ne ._)); array line[*] line:; call sortC(of line[*]); length line0 $8; line0 = lowcase(cats(of line[*])); if _n_ eq 1 then call symputX('F',cats('$F',dim(line),'.')); run; proc report nowd list headline data=work.mclines2; column level method,dependent,(mean line0) necessaryEvil; define level / group; define method / across 'Method' '--'; define dependent / across 'Dependent' '--'; define mean / sum ' ' format=6.3; define line0 / display ' ' format=&f; define necessaryEvil / noprint; compute after; line 'Means with the same letter are not significantly different.'; endcomp; run;

On 6/14/08, data _null_, <datanull@gmail.com> wrote: > I found data in the examples that should be pretty close to yours. > This may be something like you need. > > title 'Balanced Data from Randomized Complete Block'; > data plants; > input Type $ @; > do Block = 1 to 3; > input StemLength @; > Stem2 = StemLength+rannor(12345)*4.1; > Stem3 = StemLength+rannor(12335)*.4; > output; > end; > datalines; > Clarion 32.7 32.3 31.5 > Clinton 32.1 29.7 29.1 > Knox 35.7 35.9 33.1 > O'Neill 36.0 34.2 31.2 > Compost 31.8 28.0 29.2 > Wabash 38.2 37.8 31.9 > Webster 32.5 31.1 29.7 > ;;;; > run; > > ods trace on; > ods output mclines=mclines mclinesinfo=mclinesinfo; > proc glm order=data; > class Block Type; > model Stem: = Block Type / solution; > means Type / waller regwq; > run; > quit; > ods trace off; > > proc print data=mclines; > run; > proc report nowd list headline data=work.mclines(where=(mean ne ._)); > column level method,dependent,(mean line:) necessaryEvil; > define level / group; > define method / across 'Method' '--'; > define dependent / across 'Dependent' '--'; > define mean / sum ' ' format=6.3; > define line: / display ' ' spacing=0; > define line1 / spacing=1; > define necessaryEvil / noprint; > run; > > > On 6/13/08, jiana <u44208@uwe.uga.edu> wrote: > > Can Proc Report create a table means like the following: > > > > sample1 sample2 sample3 > > v1 acidity 5.7 C 6.7 A 6.6 BA > > v2 solids 6.3 DC 6.6 BA 6.7 A > > v3 dice 5.5 C 6.6 A 6.6 A > > v4 color 4.5 D 5.1 BC 5.2 BAC > > > > My input file contains attribute codes (v1--v4), names (acidity--color), > > sample id (sample1--sample3), > > means and significance. These were captured from output of Duncan's test in > > Proc Glm. > > > > I can get everything except the significance (charcter data). Is this even > > possible? > > >


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