Merging many to one

[Denise Vella]

Hello there I'm using merge - the 1:m command. Procedureno is the unique number, BUT there are duplicates in the Hospital dataset.
So I would like to merge to the proceduredata set and compare the dates. Bascially keep the procedureidno observations with the closest date to the opdate.

Q1, As you can see both datasets all have unique variables except: gender and procedureidno - so why does it says Matched(3) - should it not say Matched(2) - as these are the only common variables.

Q2. I also have unique string variables in the hospitaldataset which are not shown here labelled 'implantdetail'. The 'implantdetail' is not present in the proceduredataset. I assume this won't create a problem whilst merging but the dataset will just create a column with the string variable?


Here are the datasets

Hospital Dataset

* Example generated by -dataex-. For more info, type help dataex
clear
input double procedureno long gender2 float opdate
220 1 22271
220 1 22273
221 2 22281
221 2 22282
221 2 22282
223 1 22312
end
format %td opdate
label values gender2 gender2
label def gender2 1 "F", modify
label def gender2 2 "M", modify

Procedure dataset - this is the master dataset

* Example generated by -dataex-. For more info, type help dataex
clear
input double procedureno long gender2 float date
220 1 22271
221 2 22281
223 1 22312
end
format %td date
label values gender2 gender2
label def gender2 1 "F", modify
label def gender2 2 "M", modify

Code used:
merge 1:m procedureno using "sourceoffile.dta"

Merged dataset

* Example generated by -dataex-. For more info, type help dataex
clear
input double procedureno long gender2 float(date opdate) byte _merge
220 1 22271 22271 3
221 2 22281 22281 3
223 1 22312 22312 3
220 1 22271 22273 3
221 2 22281 22282 3
221 2 22281 22282 3
end
format %td date
format %td opdate
label values gender2 gender2
label def gender2 1 "F", modify
label def gender2 2 "M", modify
label values _merge _merge
label def _merge 3 "Matched (3)", modify

[Andrew Musau]

The _merge variable is categorical and the labels just define the categories. A value of 3 represents matched observations.

Numeric Equivalent
code word (results) Description
-------------------------------------------------------------------
1 master observation appeared in master only
2 using observation appeared in using only
3 match observation appeared in both

4 match_update observation appeared in both,
missing values updated
5 match_conflict observation appeared in both,
conflicting nonmissing values
-------------------------------------------------------------------

See

help merge