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Re: st: Adding a new variable to update a class of observations
To Robin Newberry,
How big is this spreadsheet that tracks the changes? What form is it in --
wide or long? Do you have it as a Stata dataset?
If the changes are small in number, then you can write some
generate/replace expressions to do what you want. Otherwise, you need to
put the "spreadsheet that tracks these changes" into a Stata dataset in a
sufficiently-organized form. It should have a variable with all the
various department identifiers (which ought to be unique-valued), and
another with the "condensed" identifiers (one value for each
actually-distinct department). Then merge this to your main dataset.
You mentioned two variables -- a department name and a department
number. The operation I sketched should apply to only one of these -- at
least in terms of the match key. Presumably, the name is functionally
dependent on the number, making for non-normal data; you may want to factor
out the department name.
At 04:12 PM 3/8/2005 -0500, you wrote:
I have some variables which denotes a sub-set of observations in the
injury data which groups employees working together; typically there's a
"department name" and a "department number". The issue is that the names
and numbers identifying these categories have changed repeatedly over the
last 15 years. An employee may have started out working in "Department A"
progressed through departments B, C, and D without ever actually changing
jobs, supervisors, etc. - all that's changed is the nomenclature. I don't
believe we've ever duplicated and inadvertently renamed "Department A" to
"Department D", then later renaming another group "Department A".
Somewhere we have a spreadsheet that tracks these changes, and I'd like to
incorporate the changes to more or less normalize the data; that way I can
track injuries amongst the folks who mow the grass, regardless of what
their department is called. Is there a way to add a new variable, and
equate it to an existing one?
W. Robert Newberry, IV CIH, CHMM
Chief Environmental Health and Safety Officer
Institute for Policy Studies
Johns Hopkins University
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