Imagine there is a group of people numbered 1-100, each of which have a few numerical attributes e.g. height, weight, age.
There is a small sub-group
(A) which consists of 10 people from the bigger group, say 1-10. The group does not necessarily have anything in common in terms of the attributes.
What I would like to do is find a new sub-group
(B), also 10 people among the rest of the group (11-100) that are most similar to the group
(A) in terms of the attributes height, weight, age.
What approach would you take on this?
I thought of doing some euclidian distance matrix person-person, and then matching them up 1 to 1 - but is that really the way to go?
BACKSTORY: In lack of an actual experiment - group
A is a set of users who did something and I want to have a group
B which were similar to
A but did not do that something, i.e. a "control"-group of sorts to estimate the effect of what