One of Stata’s great strengths is its data management abilities. When either building or sharing datasets, some of the most time-consuming activities are validating the data and writing documentation for the data. Much of this futility could be avoided if datasets were self-contained, i.e., if they could validate themselves. I will show how to achieve this goal within Stata. I will demonstrate a package of commands for attaching validation rules to the variables themselves, via characteristics, along with commands for running error checks and marking suspicious observations in the dataset. The validation system is flexible enough that simple checks continue to work even if variable names change or if the data are reshaped, and it is rich enough that validation may depend on other variables in the dataset. Since the validation is at the variable level, the self-validation also works if variables are recombined with data from other datasets. With these tools, Stata’s datasets can become truly self-contained.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.