>
> I am stuck with the experiment design of my dissertation. My experiment
> would like to investigate the influences of different factors of stimuli
> on the subject's response (each factor is a continuous variable), and
> further build a regression model for these relations. My questions are:
>
> 1. It seems that no experiment-design issues related to Regression
> Analysis are discussed in the usual statistics textbook. Why? Does it
> mean one needn't consider the experiment design if he uses Regression
> Analysis to analyze his data?
Regression analysis is the fundamental technique
by which experiments are analyzed. You can and
should construct an experimental design precisely
for the model you choose. You cam find
experimental designs in any book on the topic. Box
and Hunter is a standard text for engineers. It an
others will suggest designs. The use of such
designs will greatly improve your changes of
success; however, if you have a specific model in
mind, you may find such "packaged" designs
unsuitable, since they assume specific simple
models that may not be to your liking. You can
construct a design for precisely your model using
any of a number of statistical software packages
-- look for one with an optimum design algorithm.
You might like to seek out a copy of Atkinson and
Donev. The first part is quite elementary and
should prove useful in this matter.
It is extremely important that you choose a sample
size adequate to detect differences of prickle
importance. Just because a design requiems N
observations, does not been that this is the right
size. Make a power calculation before you begin
and save yourself some headache.
>
> 2. Due to the measure of the dependent variable is the participants'
> subjective responses, to remove unrelated subject-specific variables, I
> am considering to employ a within-subject design. But there seems no
> statistical packages ready for dealing with within-subject design of
> Regression Analysis?
>
> Suppose a design in which each of the n subjects gives rise to a Y
> observation under each of c different conditions, then a total of N=ncY
> observations could be obtained. How can I use Regression Analysis to
> analyze these observations?
Many statistical packages deal with this. Look for
routines that deal with "split plots" or "nested
responses." In addition if there is a structure
of some sort within subjects, then you should
consider summarizing the within subject data into
several variables and analyzing each separately.
There is much more than can be done, but this will
start you off.
>
> Thanks for your help.
>
> Wen-Feng
>
--
Bob Wheeler --- (Reply to: [EMAIL PROTECTED])
ECHIP, Inc.
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