Hi,
A while ago I received the suggestions below from this newsgroup,
which was most helpful. I proceeded to do an intrablock analysis,
which worked out fine. However, upon rereading the suggestions, I am
slightly puzzled by some of what was proposed, can anyone clarify.
Jos Jansen wrote (see below for the full question and answer) "The
intrablock analysis can be performed by regression of the differences
using 2 contrast vectors for treatments differences (a third would be
redundant), and 3 contrast vectors for sequence effects (one for each
treatment combination)."
I understand how to calculate differences (:->), but I am not sure
what "regression of the differences using 2 contrast vectors for
treatments differences" means. If I were to that in, say SPSS, how
would I proceed? I gather I should still use the grp factor (perhaps
encoded into some dummy variable?), but how could I set up the
contrasts that tests for treatment differences?
If the above question is too basic, perhaps someone can point me to
information that can help answer it?
Thanks in advance,
Kasper Hornb�k
---0---
Fra:Jos Jansen ([EMAIL PROTECTED])
Emne:Re: Analysis of design where subjects only use a selection of
treatment
View: Complete Thread (3 artikler)
Original Format
Nyhedsgruppe:sci.stat.edu, comp.soft-sys.stat.spss Dato:2004-02-21
04:06:37 PST
"Kasper Hornbaek" <[EMAIL PROTECTED]> schreef in bericht
news:[EMAIL PROTECTED]
> Hi,
>
> I have a question on how to analyse an exprimental design.
>
> We had three treatments (C, T, M) of which only two could be
> administred to each subject. The subjects receieved those treatments
> in two weeks following each other (W1, W2). I total there were six
> experimental groups, each defined by a treatment combination, i.e.
>
> grp w1 w2
> 1 C T
> 2 C M
> 3 T C
> 4 T M
> 5 M C
> 6 M T
>
> We are interested in comparing the effects of treatments, e.g. C vs M.
> Right now I am considering a repeated measures analysis, with week and
> grp as factors. However, I cannot figure out how to compose the
> contrasts that would answer our questions.
>
> Any hints? Is there some other, conceptually easier approach I could
> take? Any litterature on this?
This experimental design is a balanced incomplete block design, with
subjects being the blocks . A description of the analysis can be found
in any standard book on experimental design and the analysis can
probably best be performed by standard software for this type of
design. There are two possibilities: intrablock analysis, and analysis
with 'recovery of interblock information'. The latter is, in fact, a
mixed model analysis.
For this special case one could equivalently proceed according to the
following lines (I suppose that treatment combinations have been
randomly assigned to subjects). Calculate differences and sums per
subject. The intrablock analysis can be performed by regression of the
differences using 2 contrast vectors for treatments differences (a
third would be redundant), and 3 contrast vectors for sequence effects
(one for each treatment combination). The interblock analysis can be
performed similarly by regression analysis of the sums. The estimates
from intra- and interblock analysis may eventually be combined, using
the inverse of estmated variances as weights; this may be not
worthwile, since the interblock estimates probably are much less
precise than the intrablock estimates.
This analysis covers all aspects that have been touched in posts by
Jim Clark and Donald Burrill.
Jos Jansen
.
.
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