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Recruiting & training data entry clerks

Aim To secure accurate data entry by recruiting and training data entry clerks. Requirements Qualification list for recruiting data entry clerks Training protocol including requirements regarding intra- and inter-observer agreement Training…

https://aph-qualityhandbook.org/set-up-conduct/methods-data-collection/2-2-quantitative-research/2-2-1-preparation/recruiting-training-data-entry-clerks/

Data entry accuracy

To explain how to determine the accuracy of data entry. Requirements Non WMO research Prior to data cleaning, researchers should evaluate the data entry error of their data; If the amount of errors discovered by data entry evaluation is larger than…

https://aph-qualityhandbook.org/set-up-conduct/process-analyze-data/3-2-quantitative-research/3-2-1-data-processing/data-entry-accuracy/

Data entry methods

and corresponding computer program for data entry (including online data collection). In choosing, one should take into consideration the types of data, research population, risk of data entry errors, research processes, privacy, (GCP) regulations,…

https://aph-qualityhandbook.org/set-up-conduct/methods-data-collection/2-2-quantitative-research/2-2-1-preparation/data-entry-methods/

Supporting & monitoring data entry clerks

To secure high quality of data by accurate data entry, by supporting the data entry clerks and monitor their data. Requirements Standardized data entry procedures, including how to cope with missing data; Quality monitoring of first set of data…

https://aph-qualityhandbook.org/set-up-conduct/methods-data-collection/2-2-quantitative-research/2-2-5-data-collection/supporting-monitoring-data-entry-clerks/

Data cleaning and transformation

during data collection, please refer to Data entry accuracy Documentation Note all modifications in the syntax/code file and reasons and impact assessment of such a change in RDM F04 Change Management (intranet) to ensure you show careful processing…

https://aph-qualityhandbook.org/set-up-conduct/process-analyze-data/3-2-quantitative-research/3-2-1-data-processing/data-cleaning-and-transformation/

Handling missing data

Random missing values may also result from data entry mistakes. Non-random missing values may occur because subjects purposefully do not answer some questions. Subjects may be reluctant to answer some questions because of social desirability…

https://aph-qualityhandbook.org/set-up-conduct/process-analyze-data/3-2-quantitative-research/3-2-2-data-analysis/handling-missing-data/

Supporting & monitoring data collectors

accurate data collection by supporting data entry staff and monitoring the data collected. Please note, that there are stricter requirements (trial master file and eCRF e.g.) for Clinical Trials with pharmaceuticals and Medical devices that fall…

https://aph-qualityhandbook.org/set-up-conduct/methods-data-collection/2-2-quantitative-research/2-2-5-data-collection/supporting-monitoring-data-collectors/

Data provided by third parties

been created? Is there a code book? Was the data entry monitored? Have many errors been identified and how have these been corrected? Have the data been cleaned? If so, how? Inspect the data for completeness and odd findings, such as unusual…

https://aph-qualityhandbook.org/set-up-conduct/methods-data-collection/2-2-quantitative-research/2-2-5-data-collection/data-provided-by-third-parties/