Data validation and other strategies for data entry

West J Nurs Res. 2015 Apr;37(4):546-56. doi: 10.1177/0193945914532550. Epub 2014 Apr 29.

Abstract

Data entry can result in errors that cause analytic problems and delays in disseminating research. Invalid responses can lead to incorrect statistics and statistical conclusions. The purpose of this article is to provide researchers some basic strategies for avoiding out-of-range data entry errors and streamlining data collection. This article identifies some basic strategies using Microsoft® Excel, which is an inexpensive method of data entry that can be used when research budgets are constrained. Data files can be structured so that out-of-range values cannot be entered. When string variables are entered, researchers may be inconsistent in the way they code responses. Data validation can be accomplished through the use of restricting response options and skipping items can be avoided by using count functions to tabulate the number of valid responses. We also discuss advantages and disadvantages of several methods of data entry, including using web-based data entry and relational databases.

Keywords: data entry; descriptive quantitative; gerontology; instrument development; methods.

MeSH terms

  • Data Accuracy*
  • Data Collection / methods*
  • Data Collection / standards*
  • Data Interpretation, Statistical*
  • Databases, Factual / standards*
  • Humans
  • Qualitative Research