Date: Wed, 10 May 2006 14:48:00 +0200
Reply-To: Antonio <amaurand@um.es>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Antonio <amaurand@um.es>
Subject: Re: spssx --- euclidean based MDS (MultiDimensinal Scalling)
In-Reply-To: <E08B564BAA29FE4F8EC8BAF42FE0A01F01054F03@bubsex02.cen.csin.cz>
Content-Type: text/plain; charset=ISO-8859-1; format=flowed
It looks very much like what I'm looking for. I'll keep working on it.
Thank very much. Dík.
Antonio.
Thanks. Gracias. Danke. Merci. Obrigado. Grazie. Tak. Dík.
Spousta Jan escribió:
>Hi Antonio,
>
>Try something like this below (i.e.create an ident - transpose data -
>create the distance matrix - scale):
>
>Greetigs
>
>Jan
>
>
>DATA LIST free / esp trat h1 h2 h3 h4 h5 h6 h7 h8 h9 h10 h11 h12 h13
>h14 h15 h16.
>BEGIN DATA.
>1 1 2 0 0 0 0 0 0 0 0 0 0 0 0
>0 0 0
>2 1 2 2 0 0 0 0 0 0 0 0 0 0 0
>0 0 0
>3 1 6 0 4 0 0 0 0 0 0 0 0 1 0
>1 0 0
>1 4 1 5 0 8 0 0 0 1 0 0 0 0 0
>0 0 0
>2 4 32 0 0 1 0 0 0 0 0 1 1 0 0
>0 0 0
>3 4 24 14 0 1 0 0 1 0 0 0 0 0 0
>0 0 0
>1 2 21 0 0 2 0 0 0 0 0 0 0 0 0
>0 1 1
>2 2 22 1 0 0 0 0 0 0 1 0 0 0 0
>0 0 0
>3 2 28 0 0 0 0 0 1 0 0 0 0 0 0
>0 0 0
>1 3 7 1 0 0 0 1 0 0 0 0 0 0 0
>0 0 0
>2 3 0 0 0 0 0 0 0 0 0 0 0 0 0
>0 0 0
>3 3 0 0 9 0 7 1 0 0 0 0 0 0 1
>0 0 0
>END DATA.
>form all (f4).
>string ident (a5).
>compute ident = concat("E",string(esp,f1),"_T",string(trat,f1)).
>
>FLIP VARIABLES=h1 h2 h3 h4 h5 h6 h7 h8 h9 h10 h11 h12 h13 h14 h15 h16
>/NEWNAME=ident .
>PROXIMITIES E1_T1 E2_T1 E3_T1 E1_T4 E2_T4 E3_T4 E1_T2 E2_T2 E3_T2 E1_T3
>E2_T3 E3_T3 /PRINT NONE /MATRIX
> OUT('C:\Temp\spssalsc.tmp')
> /MEASURE=EUCLID /STANDARDIZE=NONE /VIEW=VARIABLE .
>ALSCAL
> /MATRIX= IN('C:\Temp\spssalsc.tmp')
> /LEVEL=ORDINAL
> /CONDITION=MATRIX
> /MODEL=EUCLID
> /CRITERIA=CONVERGE(.001) STRESSMIN(.005) ITER(30) CUTOFF(0)
>DIMENS(2,2)
> /PLOT=DEFAULT ALL
> /PRINT=DATA HEADER .
>ERASE FILE='C:\Temp\spssalsc.tmp'.
>
>
>
>-----Original Message-----
>From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of
>Antonio
>Sent: Wednesday, May 10, 2006 1:06 PM
>To: SPSSX-L@LISTSERV.UGA.EDU
>Subject: spssx
>
>I want to perform am euclidean based MDS (MultiDimensinal Scalling).
>
>My problem is that I do not know how to obtain the disimilarities matrix
>iusing spss.
>
>
>I have the following dataset structure: two Independent variables (host
>(3 levels), treatment (4 levels)) and 16 dependent variables that
>represnet the amount of diferents types of bacteria I found in the roots
>of 212 samples. I'd like to stuady the similarities or dissimilarityes
>between diferent treatments or different hosts.
>
>Firts, I know I have to transform my matrix into a inferior triangular
>(or symeytric) one using the euclidean distance, but how?
>
>Here is my dataset:
>
>DATA LIST LIST/esp trat h1 h2 h3 h3 h4 h5 h6 h7 h8 h9 h10 h12 h13 h13
>h14 h15 h16
>BEGIN DATA
>1 1 2 0 0 0 0 0 0 0 0 0 0 0
>0 0 0 0
>2 1 2 2 0 0 0 0 0 0 0 0 0 0
>0 0 0 0
>3 1 6 0 4 0 0 0 0 0 0 0 0 1
>0 1 0
>1 4 1 5 0 8 0 0 0 1 0 0 0 0
>0 0 0 0
>2 4 32 0 0 1 0 0 0 0 0 1 1 0
>0 0 0 0
>3 4 24 14 0 1 0 0 1 0 0 0 0 0
>0 0 0 0
>1 2 21 0 0 2 0 0 0 0 0 0 0 0
>0 0 1 1
>2 2 22 1 0 0 0 0 0 0 1 0 0 0
>0 0 0 0
>3 2 28 0 0 0 0 0 1 0 0 0 0 0
>0 0 0 0
>1 3 7 1 0 0 0 1 0 0 0 0 0 0
>0 0 0 0
>2 3 0 0 0 0 0 0 0 0 0 0 0 0
>0 0 0 0
>3 3 0 0 9 0 7 1 0 0 0 0 0 0
>1 0 0 0
>END DATA.
>
>Antonio.
>Thanks. Gracias. Danke. Merci. Obrigado. Grazie. Tak.
>
>
>
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