You are failing to take account of one or more additional variables in your data set that, combined with the variables you are trying to use as the merge key, uniquely identify the observations in one or both of your data sets, so you can use merge 1:m or merge m:1 or merge 1:1 with the expanded merge key.ģ. Your merge key actually does uniquely identify the observations in one of your data sets, so you can use merge 1:m or merge m:1 or maybe even merge 1:1.Ģ. If you are thinking about using merge m:m, it is a near certainty that at least one of the following is true:ġ. Tips for this are given in Troubleshooting m:m merges below. If you think that you need an m:m merge, then you probably need to work with your data so that you can use a 1:m or m:1 merge. Thus m:m merges are dependent on the current sort order-something which should never happen.īecause m:m merges are such a bad idea, we are not going to show you an example.
If the master and using have an unequal number of observations within the group, then the last observation of the shorter group is used repeatedly to match with subsequent observations of the longer group. In an m:m merge, observations are matched within equal values of the key variable(s), with the first observation being matched to the first the second, to the second and so on. M:m specifies a many-to-many merge and is a bad idea.
#M&M3E M&M GENERATOR MANUAL PDF#
The following is copied word-for-word from the documentation of the merge command in the Stata Data Management Reference Manual PDF included in the Stata installation and accessible from Stata's Help menu.
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