I have an experimental setup with 2 factors, site and disturbance treatment. I have reason to suspect that plots at site A will be more affected by treatment than plots at site B. My response variable is change in the % of the plot covered by a species over time. Site A has about half the starting species cover as site B. At regular intervals, a portion of the plot is haphazardly removed through disturbance (at 3 different levels).
The response variable is created by using repeated cover measures on each plot to draw a linear regression through the points, to eliminate temporal auto-correlation and generate an independent set of response variables. The slope of this regression is the response variable, which is change in percentage of plot covered by the species per annum.
I have generally been suffering from low power. I am interested in testing the interaction of site and treatment, but am interested in using a 1 tailed test, testing if Site A is more heavily affected by treatments than site B (in other words, if sites with lower initial species cover are more affected by disturbance treatments). I can't think of a biological reason to test the other way around (that higher initial species cover would yield higher vulnerability to disturbance).
Another reason I want to use a 1 tailed test is because when I looked at the slopes of the treatments at each site, it became apparent that Site A was losing cover while Site B was remaining fairly stable.
My questions are: 1) Is it appropriate to use a one-tailed distribution to increase power in this situation? 2) Is it tautological (or logically unsound) to look at the means of each site and decide a 1-tailed test is appropriate? 3) At this point (not having yet used a 1-tailed F table but wanting to), is this decision still considered a priori? Or am i now in the post-hoc zone since the data have already been collected?
Thank you in advance for your assistance.