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• Structural Engineering Solved Problems

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Structural Engineering Solved Problems

I am in the process of merging two data sets together in Stata and came up with a potential concern. I am planning on sorting each data set in exactly the same manner on several categorical variables that are common to both sets of data. HOWEVER, several of the categorical variables have more categories present in one data set over the other. I have been careful enough to ensure that the coding matches up in both data sets (e.g. Red is coded as 1 in both data set A and B, but data set A has only Red, Green and Blue whereas data set B has Red, Green, Blue, and Yellow).

If I were to sort each data set the same way and generate an id variable ( gen id = n) and merge on that, would I run into any problems? There is no statistical question here, as this is purely about data management in Stata, so I too shall shortly vote for this to be migrated to Stack Overflow, where I would be one of those who might try to answer it, so I will do that now. What you describe to generate identifiers is not how to think of merging data sets, regardless of any of the other details in your question. Imagine any two data sets, and then in each data set, generate an identifier that is based on the observation numbers, as you propose. Generating such similar identifiers does not create a genuine merge key.

You might as well say that four values 'Alan' 'Bill' 'Christopher' 'David' in one data set can be merged with 'William' 'Xavier' 'Yulia' 'Zach' in another data set because both can be labelled with observation numbers 1 to 4. My advice is threefold:. Try what you are proposing with your data and try to understand the results. Consider whether you have something else altogether, namely an append problem.

It is quite common to confuse the two. If both of those fail, come back with a real problem and real code and real results for a small sample, rather than abstract worries.

I think I may have solved my problem - I figured I would post an answer specifically relating to the problem in case anybody has the same issue. I have two data sets: One containing information about the amount of time IT help spent at a customer and another data set with how much product a customer purchased.

Both data sets contain unique ID numbers for each company and the fiscal quarter and year that link the sets together (e.g. ID# 1001 corresponds to the same company in both data sets). Additionally, the IT data set contains unique ID numbers for each IT person and the customer purchases data set contains a unique ID number for each purchase made. I am not interested in analysis at the individual employee level, so I collapsed the IT time data set to the total sum of time spent at a given company regardless of who was there.

I was interested in merging both data sets so that I could perform analysis to estimate some sort of 'responsiveness' (or elasticity) function linking together IT time spent and products purchased. I am certain this is a case of 'merging' data because I want to add more VARIABLES not OBSERVATIONS - that is, I wish to horizontally elongate not vertically elongate my final data set. Stata 12 has many options for merging - one to one, many to one, and one to many. Supposing that I treat my IT time data set as my master and my purchases data set as my merging set, I would perform a 'm:1' or many to one merge.

This is because I have MANY purchases corresponding to one observation per quarter per company.