We would like to explore disparities in Tobacco retail locations in my county. Majority were surveyed by the local health department however, there were 16 that were not surveyed. We would like to use the surveyed location to explore the disparities however, we want to confirm that those that did not participate in the survey, are not located in areas that is potentially different from the area of those surveyed. To answer this question, I thought the best approach would be to calculate the mean centers and standard deviational ellipses ( at one standard deviation) to compare the distribution of surveyed v not surveyed. The mean centers of both, surveyed and not surveyed were within a 1/2 mile of each other however, the ellipse of the not surveyed was with in the ellipses of those surveyed. Because i am relatively new to the field, I just wanted to confirm that my interpretation of the "nested" ellipses results means that we can be confident that the information collected from the survey "speaks" to the general landscape of tobacco retail in the county. ( see attachment for reference)
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If the size and shape of the SDEs were more closely aligned … then you could say that the distributions were similar and that the surveyed and un-surveyed stores are part of the same “landscape.”
Since the ellipse for the un-surveyed locations is much smaller than the ellipse for the surveyed locations, this seems to indicate the opposite … that the un-surveyed locations are actually not representative of the entire county/study area. The fact that all of the un-surveyed locations fall into the surveyed ellipse is not sufficient evidence, however …
Hope this helps!
That all of your not surveyed fell within the standard deviation of those that were surveyed. It is quite possible that your not surveyed center and SDE would have been different if you had not surveyed points at the extremes of your data distribution
Thanks
If the size and shape of the SDEs were more closely aligned … then you could say that the distributions were similar and that the surveyed and un-surveyed stores are part of the same “landscape.”
Since the ellipse for the un-surveyed locations is much smaller than the ellipse for the surveyed locations, this seems to indicate the opposite … that the un-surveyed locations are actually not representative of the entire county/study area. The fact that all of the un-surveyed locations fall into the surveyed ellipse is not sufficient evidence, however …
Hope this helps!
Wow thanks for the detailed response!
The map attached is a rough draft. I included the schools just because I forgot to turn off the layer when I exported the map.
Survey locations were not picked, we contacted all retailers and 16 chose not to participate in the survey.
The only evidence that can indicated that these locations would not be different from closest surveyed locations or other surveyed locations is by understanding the survey data better. For example if our data exploration reviles that store type is the main factor that affects advertising, we can classify the not surveyed by store type and see if they are represented in the surveyed locations.
Sounds like you are on the right track!