=========================================================================
Date:         Wed, 26 Jul 2006 14:50:05 +0530
Reply-To:     Manmit Shrimali <MShrimali@marketrx.com>
Sender:       "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From:         Manmit Shrimali <MShrimali@marketrx.com>
Subject:      Re: pair t test for multiple variables
Content-Type: text/plain; charset="iso-8859-1"

Thanks Marta. I am sorry I posted on personal message. I am using the list serve for very first time so was not aware of whether to reply your email or listserv. Thanks again for make me informed.

Manmit
-----Original Message-----
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU] On Behalf Of Marta García-Granero
Sent: Wednesday, July 26, 2006 2:23 PM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: Re: pair t test for multiple variables

Hi Manmit

I'd rather follow this exchange of messages here, if you don't mind...

MS> Thanks Marta for the solution. I had written long syntax and
MS> it did not work. Your syntax, short and sweet works perfectly
MS> alright.

One item I forgot to mention in my previous message is the problem of
hight type I error. You're running 153 t-tests, the chance that at
least one is significant by chance is really above 0.05 (i feel lazy
right now, that's why I'm not computing it, but I know it will be over
99%: 1-(0.95^153)). An overall test (like a RM ANOVA or Friedman) can
be useful to check if there at least one pair of variables that differ
signifficantly.

MS> Re: RM GLM, you raised very important point. As per my
MS> understanding, we need to classify the dependent variable and
MS> factors. In my given problem, I cannot classify any message as
MS> dependent. Usually, when I have data in column I use pair-t test
MS> and using indepdent t-test will not generate significance
MS> different. E.g. if the data is in the following manner:

MS> Begin data
MS> Id Drug1 Drug2 Drug3 Drug4
MS> 1   7     7      7     7

(message followed...)

Sorry, but I don't quite follow your reasoning. You can, and you
should use a RM ANOVA before attempting all those paired t-tests (if
it is not significant, then you needn't perform all those pairwise
comparisons):

* Simulated data (according to your layout) *.
INPUT PROGRAM.
- VECTOR m(18).
- LOOP #I = 1 TO 20.
- LOOP #J = 1 TO 18.
- COMPUTE m(#J) = 1+TRUNC(UNIFORM(7)).
- END LOOP.
- END CASE.
- END LOOP.
- END FILE.
END INPUT PROGRAM.
FORMAT m1 TO m18 (F4).
EXE.

GLM  m1 TO m18
  /WSFACTOR = m 18 Simple
  /EMMEANS = TABLES(m)
  /WSDESIGN = m .

Concerning the second point I mentioned: your data are not truly
quantitative, but ordinal. You could try Friedman test

NPAR TESTS
  /FRIEDMAN = m1 TO m18.

--
Regards,
Dr. Marta García-Granero,PhD           mailto:biostatistics@terra.es
Statistician





--- "It is unwise to use a statistical procedure whose use one does
not understand. SPSS syntax guide cannot supply this knowledge (nor
this list), and it is certainly no substitute for the basic
understanding of statistics and statistical thinking that is essential
for the wise choice of methods and the correct interpretation of their
results".