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The lead field investigators checked the data for errors, then coded and entered it daily into a password protected Excel spreadsheet.
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Computer programs then check the data for errors.
Data screening is the procedure of checking the data for errors and fixing or removing these errors.
The most time-consuming single programming task was developing the commands that checked the data for potential errors.
Exploratory data analysis involved checking the data for implausible relationships, outliers and errors using frequency distributions, tables and graphs.
We used data at the product groups (three-digit codes) level of the Standard International Trade Classification (SITC), Revision 1 and checked these data for errors and gaps.
The input program was primarily devoted to statements that checked the entered data for potential errors.
Functionalities like checking received data for errors and requesting retransmission of garbled information can then be defined independently of the particular physical means of transmission employed.
Data coding and cleaning were performed by cross-Checking the printout data for obvious errors to assure quality of data.
Data coding, cleaning and verification were performed by cross-checking the printout data for obvious errors, (i.e. exceptionally long or short lines, blanks that should not be there, alphabetic codes where numbers are expected, obviously wrong codes) to assure quality of data.
We have demonstrated the feasibility of checking source clinical data for error, and the possibility of attaining high quality data using electronic data feeds for both prospective and retrospective parts of our data repository.
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