Hello all,

I am working on a research project and trying test an issue pre and
post an event.  I'm concerned that the distribution of my sample may
be posing a problem with my final conclusions.  I would like to see if
my concerns are legitimate.

I am comparing two samples pre and post an event.  The two samples are
Incr and Decr.  The sample distributions (# of observations) are as
follows:

Sample:      Incr   Decr
Pre-period:  13     6
Post-period: 26     18

I am running an OLS regression in SAS and I am also using a dummy to
denote 1 for the post period and 0 for the pre period to increase the
overall sample size when running the regression rather than comparing
the two samples (pre and post) separately.  Adding a dichotomous
variable may or may not be a good idea.

My regression looks like the following:

Y = D*X1 for sample Incr where D equals 1 if post and zero otherwise

Y = D*X2 for sample Decr where D equals 1 if post and zero otherwise


**Is there a way to statistically control for this imbalance in the
data for the pre and post periods??

Any comments/suggestions would be greatly appreciated.

Thanks.
.
.
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