completeness of data collection

USAGE SUMMARY

The phrase "completeness of data collection" is correct and usable in written English.
It can be used when discussing the thoroughness and adequacy of the data gathered for research or analysis purposes. Example: "The completeness of data collection is crucial for ensuring the validity of the research findings."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

26 human-written examples

Parameters measured within the feasibility trial will include recruitment and retention, practicality of collecting outcome measures, completeness of data collection, and data required for the assessment of cost-effectiveness.

BMJ Open

Two follow-up emails five days apart from each other will be sent to remind those who have not completed each survey to ensure the completeness of data collection.

BMC Health Services Research

To ensure completeness of data collection, each interviewer checked responses to questionnaires before ending each visit.

The Journal of Headache and Pain

Completeness of data collection will be stimulated by means of email reminders.

BMC Musculoskeletal Disorders

Strengths of the present study include the large study size and the completeness of data collection.

BMJ Open

Therefore, completeness of data collection, diagnostic yield, technical details and complications were ensured.

BMC Pulmonary Medicine

Human-verified similar examples from authoritative sources

Similar Expressions

33 human-written examples

Therefore, we were not able determine the extent to which the specified data elements were actually being collected or the completeness or reliability of data collection.

BMC Palliative Care

Quality, completeness and consistency of data collection are audited with feedback to the individual units.

Critical Care

The participants were contacted by trained medical students at regular intervals to verify the completeness and accuracy of data collection.

BMC Medical Education

Greater use of electronic medical records and patient management information systems has improved the completeness and uniformity of data collection systems [ 16, 17].

BMC Medical Informatics and Decision Making

At the end of the season all players filled in a questionnaire on injuries and subjective participation in the study to check the completeness and coverage of data collection.

British Medical Journal

Expert writing Tips

Best practice

When writing about research methodology, clearly define how you ensured the "completeness of data collection". This demonstrates rigor and attention to detail.

Common error

Don't assume that data collection is complete without implementing verification steps. Always include quality checks and follow-up procedures to maximize "completeness of data collection".

Linguistic Context

The phrase "completeness of data collection" functions as a noun phrase, typically serving as the subject or object of a sentence. It describes the degree to which all necessary data has been gathered. As Ludwig AI confirms, the phrase is valid and widely used in academic writing.

Expression frequency: Very common

Frequent in

Science

85%

Formal & Business

8%

News & Media

7%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

The phrase "completeness of data collection" is a grammatically correct and frequently used term, primarily in scientific and research contexts, to emphasize the thoroughness of data gathering. As Ludwig AI confirms, it's suitable for formal writing. To ensure effective communication, focus on verification and clear protocols. While alternatives like "thoroughness of data gathering" exist, "completeness of data collection" remains a standard choice in academic and professional settings. Therefore, understanding its usage and importance is crucial for researchers and analysts.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

thoroughness of data gathering

Focuses on the meticulous and exhaustive nature of the data collection process.

comprehensiveness of data assembly

Highlights the inclusive and all-encompassing aspect of gathering data.

integrity of data compilation

Emphasizes the accuracy and reliability of the compiled data.

accuracy and coverage of data acquisition

Combines the concepts of correctness and breadth in obtaining data.

exhaustiveness of data procurement

Stresses the complete and detailed nature of obtaining the data.

extent of data collation

Indicates the scope and range of the data brought together.

data collection integrity

Highlights the quality and reliability of the collected data.

data gathering completeness

Reverses the phrase structure while maintaining the same meaning.

fullness of data set

Emphasizes the extent to which the data set is filled or complete.

data sufficiency for analysis

Focuses on whether the data is adequate for conducting a thorough analysis.

FAQs

How can I ensure "completeness of data collection" in my research?

To ensure "completeness of data collection", implement rigorous data collection protocols, train data collectors thoroughly, use data validation techniques, and follow up on missing data points. Regularly monitor data collection progress to identify and address any gaps.

What are some strategies to improve "completeness of data collection"?

Strategies to improve "completeness of data collection" include using clear and concise data collection forms, providing incentives for participation, sending reminders to participants, and employing electronic data capture systems.

What is the difference between "completeness of data collection" and "accuracy of data collection"?

"Completeness of data collection" refers to ensuring all required data points are collected, while "accuracy of data collection" refers to ensuring that the data collected is correct and free from errors. Both are essential for reliable research.

Why is "completeness of data collection" important?

"Completeness of data collection" is crucial because it directly impacts the validity and reliability of research findings. Incomplete data can lead to biased results, inaccurate conclusions, and compromised decision-making.