.png){kind=icon}
.png){kind=icon}
Return
Improving data accuracy: Selecting the best data checking technique
.png){kind=icon}
PRE
AI
DOI：10.1016/j.chb.2013.02.021.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Data entry errors can have catastrophic effects on the results of a statistical analysis. Therefore, researchers often spend considerable effort checking their data. This paper compared the effectiveness of three data checking methods - double entry, read aloud, and visual checking - using the types of data and data entry personnel that are typically used in psychological research. To compare these techniques, we created 20 data sheets and entered them into the computer. Next, we deliberately introduced errors into this data set. Participants' job was to locate and correct these errors. A total of 340 undergraduates participated in this study. Of these, 80 had previous data entry experience and 260 did not. Double entry was far superior to read aloud and visual checking, both among people with previous data entry experience and among people without previous experience. Among people with no previous experience, read aloud and visual checking had more than 20 times as many errors as double entry. In addition, double entry was preferred over visual checking. Thus, although double entry takes slightly longer, it is clearly worth the extra effort. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords:
Data checking
Double entry
Read aloud
Visual checking
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
8.9
Papers:
9.0K
Citations:
5.8W