How to merge data in stata - merge

Question

I'm learning stata, and trying to understand merging. Can someone explain the difference between different kinds of merging to me? (1:1, 1:m, m:1, m:m)?

Answer 1

In case the Stata manual is unclear, here's a quick overview.
First, it's important to clear up the terminology.
A merge basically connects rows in two datasets (Stata calls them observations) based on a specified variable or list of variables, called key variables. You have to start with one dataset already in memory (Stata calls this the master dataset), and you merge another dataset to it (the other dataset is called the using dataset). What you're left with is a single dataset containing all of the variables from the master, and any variable from the using that didn't already exist in master. It also generates a new variable called _merge indicating whether there were rows in master that weren't in using or vice versa. The merged dataset (unless otherwise specified) will contain all rows from master and using, regardless of whether the key variables matched between the two.
The concept of a "unique identifier" is important. If a variable (or combination of variables) has a different value in every row, it uniquely identifies rows. This is important for the details about 1:1, 1:m etc.
1:1 means the key variable provides unique identifiers in both datasets. You will be left with all of the rows from both datasets in memory.
1:m means the key variable in the master dataset uniquely identifies rows, but the key variable from the using dataset doesn't. You will still be left with all of the rows from both datasets, but if a key variable has duplicate observations in the using dataset, the master dataset will gain duplicates to match them.
m:1 is the opposite of 1:m. The key variable in the master dataset doesn't uniquely identify rows, but the key variable in the using dataset does.
m:m is kind of weird. The key variable doesn't uniquely identify rows in either dataset, so you will be left with duplicated rows from both sides.
Example:
** make a dataset and save as a tempfile called `b'. Note that k uniquely identifies rows
set obs 3
gen k = _n
gen b = "b"
list
+-------+
| k b |
|-------|
1. | 1 b |
2. | 2 b |
3. | 3 b |
+-------+
tempfile b
save `b'
** make another dataset and merge `b' to it. Note that k uniquely identifies rows
set obs 3
gen k = _n
gen a = "a"
list
+-------+
| k a |
|-------|
1. | 1 a |
2. | 2 a |
3. | 3 a |
+-------+
merge 1:1 k using `b'
list
+-------------------------+
| k a b _merge |
|-------------------------|
1. | 1 a b matched (3) |
2. | 2 a b matched (3) |
3. | 3 a b matched (3) |
+-------------------------+
** make another dataset and merge `b' to it. Note that k does not uniquely identify rows and that k=2 and k=3 do not exist in the master dataset
clear
set obs 3
gen k = 1
gen a = "a"
list
+-------+
| k a |
|-------|
1. | 1 a |
2. | 1 a |
3. | 1 a |
+-------+
merge m:1 k using `b'
list
+----------------------------+
| k a b _merge |
|----------------------------|
1. | 1 a b matched (3) |
2. | 1 a b matched (3) |
3. | 1 a b matched (3) |
4. | 2 b using only (2) |
5. | 3 b using only (2) |
+----------------------------+