Hello,
I am attempting to use a BACI design to analyze data collected to evaluate the effectiveness of a restoration project.  An example of the data is shown below where the response variable is streambank migration rate (m/yr).  I recently found a variation of BACI called MBACI, where there is replication over space instead of time as is the case with traditional BACI.  This works well for this data because I only have a "before" and an "after" time step for migration rate, but I have multiple control and impact sites where the response was measured.  This model includes a location variable, where location is nested within treatment.  
 
 
ID  trt  Location    Time  migration rate    
JF  C  C1    Before  -0.511   
JR  C  C2    Before  -0.3733   
SRR  C  C3    Before  -0.25258   
 
I used the following code (below) to run the model and the results don't exactly make sense because the F value for the trt*time interaction is extremely small.  I truly don't expect it to be significant based on some other analyses, but think such a small F value must indicate that I have problems. 
mig.aov7=aov(migration.rate~trt*Time+trt/Location)
         Df  Sum Sq  Mean Sq   F value Pr(>F)
trt          1 0.07147 0.071475    2.7420 0.1321
Time         1 0.00212 0.002120    0.0813 0.7819
trt:Time     1 0.00000 0.000001 2.451e-05 0.9962
trt:Location 9 0.35393 0.039326    1.5086 0.2749
Residuals    9 0.23460 0.026067 
 
I am also confused about the the purpose of the location variable and whether or not it should be nested as specified in the model above or if it should be included in the model at all.
 
Any help with these problems will be greatly appreciated.
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