Identical continouous dependant variables vs. unique independent variables?


New Member
Hi guys,

I'm having an issue re: the statistical test I should be using in research I am undertaking.

Let's say I have a study population of 300 subjects. Each of these subjects have an individual measure of health, let's say Forced Vital Capacity (FVC) which is a continuous measure. I wish to investigate how the distance from their home and workplace to a pollution source (a continuous measure) influences their FVC. Each subject lives in a separate home, but the subjects are from 5 different workplaces each employing 60 of them.

To investigate distance from the subjects' home to the pollution source I used simple linear regression with 'distance from home to pollution source' as the dependent variable and 'FVC' as the independent variable.

I now wish to do the same for workplaces, but for 'distance from workplace to pollution source', the dependent variable is the same value for the subjects sharing the same workplace e.g. as there are only 5 workplaces there are 5 unique distance measurements (even though they all have unique FVC measurements).

Is this an issue, and if so, how would I go about comparing subjects' 'distance from workplace to a pollution source' to their FVC?

I would like to do so independently of their home as well as including both 'distance from home and distance from workplace to a pollution source' together.

Thanks :)
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Then everybody on the same workplace would have the same exposure (and that is an explanatory variable, an independent variable). Also, try to search for land use regression.


Less is more. Stay pure. Stay poor.
Yes, I agree with GG that you seem to have mixed up your terms. I would imagine that you want to see if distance predicts FVC, not that FVC predicts distance.

You may want to run a mixed model (hierarchical linear regression), controlling for the random effects of workplace clusters.