Date: Fri, 4 Apr 2008 18:08:09 +0200
Reply-To: Marta García-Granero <email@example.com>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Marta García-Granero <firstname.lastname@example.org>
Subject: Re: Standardizing data
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I am a bit confused by your description, but I think your data look like
Day Ratio1 Ratio2 Ratio3 Ratio4 Ratio5 Ratio6
1 . . .
A randomized block design (K dependent samples, quantitative variables...).
If the data layout looks as above, to run UNIANOVA you must first stack
your dataset using VARSTOCASES (ask for help if you need it). The
UNIANOVA syntax should then look like this
UNIANOVA RadioUpt BY Ratio Days
/DESIGN= Ratio Days.
The residuals shoul be checked for normality:
/PLOT BOXPLOT STEMLEAF NPPLOT
If your data are very clearly non-normal (skewed or with extreme
outliers), then you should use Friedman test instead. The original data
layout (without stacking it using VARSTOCASES) is the one you will use
to run that procedure. If Friedman test is significant, then use
pairwise sign tests (don't use Wilcoxon, unless your data are fairly
simmetric and you use Quade test for overall significance), followed by
some p-value adjustment method (like Dunn-Sidak or Holm). Again, ask for
code to run that last task if you need it, I'll send it tomorrow (I'm
calling it a day right now and will be turning my computer off after I
Saying goodbye before hitting Send and shutting down ;)
>> Cells were cultured in 6 different mediums
>> containing different ratios of chemicals A and B
>> (1:1, 1:2, 1:3, etc). The base of the medium was
>> made at one time, separated into 6 trays, and a
>> different A:B ratio reagent was added to each of
>> the 6 trays followed by the addition of the
>> cells. This whole setup was done 5 times, i.e. on 5 different days.
>> The study question was whether the different A:B
>> ratios result in a difference in radioactive
>> uptake (a continuous variable) by the cells.
>> [...] He was going to perform a t-test to
>> identify a difference in mean between the 1:1
>> medium and each of the other mediums.
> To start with, that isn't what he wants to do. As
> described, it's a three-level one-way ANOVA, and
> should be analyzed as such, once, rather than a
> couple of t-tests. Look at ONEWAY. To then decide
> which conditions (A:B ratios) show significant
> differences from each other, use the POSTHOC
> subcommand. Among the post-hoc tests, I see that
> Marta García-Granero recommends SNK or Tukey(*).
>> However, due to the issues intrinsic in the
>> medium creation, the values vary quite
>> dramatically from day to day. Therefore, the
>> medium created on day 1 might have values in the
>> 0.5 to 2.0 range, while medium created on day 2
>> might have values in the 12.0 to 14.0 range,
>> medium created on day 3 might have values in the 3.0-5.0 range, and
>> so on.
>> My question is what would be the best way to standardize these values?
> You don't. You now have two factors: base medium
> (day), and A:B ratio. Medium day will be a random effect.
> Look at UNIANOVA. It may be as simple as
> UNIANOVA RadioUpt BY Medium Ratio
> /RANDOM Medium
> /POSTHOC <as for ONEWAY>.
> Possibly this (or ONEWAY, or both) can be clicked
> up from the menus; I do less of that.
> -Good luck,
> See the flowchart for choosing analytic
> procedures that Marta has just posted:
> http://gjyp.nl/marta/Flowchart%20(English).pdf, as noted in her posting
> Date: Fri, 4 Apr 2008 12:35:55 +0200
> From: Marta García-Granero <email@example.com>
> Subject: Flowchart already hosted!
> To: SPSSX-L@LISTSERV.UGA.EDU
> And, our thanks to Gjalt-Jorn Peters for hosting it!
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