My personal opinion is also against usage of this subcommand, and I instead recommend using the joinby command for context described here.Īppend is a STATA command that you should use when you want to ‘stack’ two or more files so they come ‘on top’ of each other. m-to-m merge is hard to use and not recommended by many STATA users. Lastly, m-to-m merge is a variation of merge command which should be used when neither of the files is unique at merge variables level.
STATA COMMANDS CODE
we will start with gender data which is unique at individual level, and merge it with height data which is unique at individual/year level.Īssuming the first file is called gender and the second height, this is the code you would use for merging: use gender, clear Here we can use the same example as in the previous step, but the difference will be in what is the master file (the first data) and what is the using file (the second data). One-to-m merge is basically an inverse of m-to-one merge. So M observations in the first file correspond to 1 (one) observations in the second file, hence the m:1 merge.Īssuming the first file is called height and the second gender, this is the code you would use for merging: use height, clear In other words, while one file contains data at individual/year level, the other contains data at individual level. As depicted in the example below, in the first file one observation corresponds to an individual at a certain point in time, while in the second file one observation corresponds to an individual. M-to-one merge is a variation of this command that you should use when one of the two files you are aiming to combine is not uniquely identified by the merge variable. Merge 1:1 name year using weight m:1 MERGE Now individual’s name does not uniquely identify observations in the two files, but name year variables combination does, so it is still a one-to-one merge. Now imagine a case where we observe height and weight of different individuals at different points in time. Merge 1:1 name using weight 1:1 MERGE (merge on multiple variables) there are no repeating names in either of the files.Īssuming the first file is called height and the second weight, this is the code you would use for merging: use height, clear
Referring to the example below where merging is done using the name variable, this means that all values of this variable should be unique, i.e. It should be used when the merge variable(s) uniquely identify both datasets that you want to merge. 1:1 MERGEġ:1 merge is the simplest variation of the merge command. Merge has four variations: 1:1 (one-to-one), m:1 (m-to-one), 1:m (one-to-m), and m:m (m-to-m). This is a command you should use when combining two files that have common identifiers into one single file. We start with the most commonly used STATA data management command – merge. The post will focus on the first four while reshape will be addressed in a separate post as it deserves separate attention. Some, but not all, of STATA data transformation commands are merge, append, joinby, cross, and reshape. The motivation for this post lies in the fact that researches are often not sure about what command they should use, or they do their work the hard way for being unaware of other more practical commands. This page aims to summarize several different data transformation commands available in STATA and to explain the context where each of those could be used.
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