Literature DB >> 30859478

Comparing the accuracy and speed of four data-checking methods.

Kimberly A Barchard1, Andrew J Freeman2, Elizabeth Ochoa2, Amber K Stephens2.   

Abstract

Double entry locates and corrects more data-entry errors than does visual checking or reading the data out loud with a partner. However, many researchers do not use double entry, because it is substantially slower. Therefore, in this study we examined the speed and accuracy of solo read aloud, which has never before been examined and might be faster than double entry. To compare these four methods, we deliberately introduced errors while entering 20 data sheets and then asked 412 randomly assigned undergraduates to locate and correct these errors. Double entry was significantly and substantially more accurate than the other data-checking methods. However, the double-entry participants still made some errors. Close examination revealed that whenever double-entry participants made errors, they made the two sets of entries match, sometimes by introducing new errors into the dataset. This suggests that double entry can be improved by focusing attention on making entries match the original data sheets (rather than each other), perhaps by using a new person for mismatch correction. Solo read aloud was faster than double entry, but not as accurate. Double entry remains the gold standard in data-checking methods. However, solo read aloud was often substantially more accurate than partner read aloud and was more accurate than visual checking for one type of data. Therefore, when double entry is not possible, we recommend that researchers use solo read aloud or visual checking.

Entities:  

Keywords:  Data checking; Data entry; Double entry; Read aloud; Visual checking

Mesh:

Year:  2020        PMID: 30859478     DOI: 10.3758/s13428-019-01207-3

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  10 in total

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Authors:  Qing-Bin Gao; Yu Kong; Zheng Fu; Jian Lu; Cheng Wu; Zhi-Chao Jin; Jia He
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Journal:  Control Clin Trials       Date:  1994-12

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Journal:  Qual Assur       Date:  1994-09

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Authors:  Miyuki Kawado; Shiro Hinotsu; Yutaka Matsuyama; Takuhiro Yamaguchi; Shuji Hashimoto; Yasuo Ohashi
Journal:  Control Clin Trials       Date:  2003-10

8.  Characteristics of eye movements in 3-D object learning: comparison between within-modal and cross-modal object recognition.

Authors:  Yoshiyuki Ueda; Jun Saiki
Journal:  Perception       Date:  2012       Impact factor: 1.490

9.  Comparison of electronic data capture (EDC) with the standard data capture method for clinical trial data.

Authors:  Brigitte Walther; Safayet Hossin; John Townend; Neil Abernethy; David Parker; David Jeffries
Journal:  PLoS One       Date:  2011-09-23       Impact factor: 3.240

10.  Quality of data entry using single entry, double entry and automated forms processing--an example based on a study of patient-reported outcomes.

Authors:  Aksel Paulsen; Søren Overgaard; Jens Martin Lauritsen
Journal:  PLoS One       Date:  2012-04-06       Impact factor: 3.240

  10 in total
  1 in total

1.  Evaluating the validity of the Amharic Brief Pain Inventory among people with chronic primary musculoskeletal pain in Ethiopia.

Authors:  Abey Bekele Abebe; Tadesse Awoke Ayele; Jordan Miller
Journal:  BMC Musculoskelet Disord       Date:  2022-09-21       Impact factor: 2.562

  1 in total

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