SPSS Matching Case Control 1:n - matching

Question

We want to match our cases and controls using SPSS 23.
We already matched our cases and controls on age in a 1:3 ratio and a tolerance of 1 month as followed:
DATASET ACTIVATE DataSet1.
FUZZY BY=Age SUPPLIERID=Databasenr NEWDEMANDERIDVARS=MatchID1 MatchID2 MatchID3 GROUP=Case FUZZ=1
EXACTPRIORITY=TRUE
MATCHGROUPVAR=Matchgroupvariable
/OPTIONS SAMPLEWITHREPLACEMENT=FALSE MINIMIZEMEMORY=FALSE SHUFFLE=TRUE.
Know we have 2 questions:
We want to use different tolerances for our cases. For example the cases aged under 1 year should be matched with a tolerance of 1 month and the cases older than 1 year with a tolerance of 6 month. How can we do that?
We want to distribute the controles equally on the cases. So we have 60 cases and 300 controles. First we want every case to have a control if possible, than we want to distribute the lasting controles equally on the cases so that every case has at least one and as many as possible controles.
Thanks for your help.

Answer 1

In order to have a fuzz that is more complex than a simple difference, you need to use a customfuzz function written in Python the computes the match criteria. I have shown a function for this below. Save this in a file named customfuzz.py somewhere that Python can find it, such as the python\lib\site-packages directory under your Statistics installation.
Then use CUSTOMMATCH='customfuzz.custommatch' in the FUZZY syntax instead of FUZZ.
Here is the function. The indentation shown is important. The code assumes that the ages are in years (which can include a fractional part).
custommatch(demander, supplier):
"""calculate match for one variable and return 0 or 1
demander and supplier are assumed to be (lists) of ages in years"""
# check for missing values
if demander[0] is None or supplier[0] is None:
return 0 # no match
delta = abs(demander[0] - supplier[0]) # difference in years
if demander[0] < 1: # demander age lt 1 year
if delta <= .08333: # difference le 1 month
return 1 # ok match
else:
return 0
else:
if delta <= .5: # difference le half year
return 1 # ok match
else:
return 0
For the second problem, what you would have to do is the first match round and then remove all the controls that were actually used and repeat the process with the reduced dataset of controls.