VOLUME 53 , ISSUE 3 ( July-September, 2019 ) > List of Articles
Citation Information : Statistics Corner: Data Cleaning-I. J Postgrad Med Edu Res 2019; 53 (3):130-132.
DOI: 10.5005/jp-journals-10028-1330
License: CC BY-NC 4.0
Published Online: 01-12-2018
Copyright Statement: Copyright © 2019; The Author(s).
Reality check “Let us assume that an investigator collected various demographic, clinical, psychiatric, and radiological characteristics of the study participants.” The investigator took adequate precautions to enter data in a structured format into a spreadsheet. However, before proceeding ahead, the investigator wanted to ensure that data are ready for analysis. In this context, the investigator reviewed the literature and came across the term “data cleaning.” The fellow colleagues advised him to approach a statistician for cleaning and analyses of the data. The investigator was in dilemma, whether to share the data with a statistician before or after cleaning. The investigator reviewed the literature and found some answers regarding the role and responsibilities of the investigator in data cleaning. However, the investigator still had the following questions for data cleaning. • Is data cleaning practice a part of good clinical practice (GCP)? • Is it the responsibility of a statistician to clean and code the data? • Do data cleaning begin after data entry? • How to deal with missing values at the data entry stage?