due to missing data

USAGE SUMMARY

"due to missing data" is a perfectly acceptable phrase and is used frequently in written English.
You can use it when referring to the partial or total absence of information or data. For example, "The team was unable to analyze the results from the survey due to missing data."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Lactate was not included due to missing data.

Annals of Intensive Care

Limitations: The number of patients excluded from the study due to missing data is substantial.

Journal of Affective Disorders

The multiple imputation technique was used in this analysis to avoid bias due to missing data.

Journal of Dairy Science

a different values due to missing data.

BMC Infectious Diseases

*Denominators may vary due to missing data.

BMC Complementary and Alternative Medicine

Participants' exclusion due to missing data.

BMJ Open

*Differences in N due to missing data.

BMC Health Services Research

N varies due to missing data.

BMC Infectious Diseases

Note: Numbers vary due to missing data.

BMC Cancer

*: Sample sizes vary due to missing data.

BMC Medical Research Methodology

Numbers vary due to missing data.

BMC Cancer

Expert writing Tips

Best practice

When using "due to missing data", clearly specify which data is missing and, if possible, the potential impact on your analysis or conclusions.

Common error

Avoid assuming that missing data is randomly distributed without proper investigation. Non-random missingness can introduce bias into your results. Always consider conducting a missing data analysis.

Linguistic Context

The phrase "due to missing data" functions as an adverbial phrase indicating the reason or cause for a particular outcome or situation. It introduces an explanation for why certain information is absent or incomplete. Ludwig confirms this is a correct grammatical structure.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Encyclopedias

0%

Ludwig's WRAP-UP

The phrase "due to missing data" is a common and grammatically sound expression used to explain limitations or variations in datasets. As Ludwig indicates, its primary function is to provide a causal explanation in formal and scientific contexts. When employing this phrase, clarity and specificity are crucial; you need to clearly state which data is missing and consider the potential biases it might introduce. Alternatives like "owing to incomplete data" or "as a result of data unavailability" can be used for variety, but maintaining a consistent and professional tone is crucial in academic and scientific writing.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

owing to incomplete data

Replaces "due to" with "owing to" and "missing" with "incomplete", slightly formalizing the tone.

as a result of data unavailability

Substitutes "missing" with "unavailability", emphasizing the lack of accessible data.

because of the absence of data

Rephrases the cause, highlighting the absence as the reason for the situation.

attributable to data gaps

Uses "attributable to" instead of "due to" and "gaps" for "missing", providing a slightly different nuance.

caused by data deficiencies

Replaces "missing" with "deficiencies", focusing on the inadequacy of the data.

stemming from data omissions

Emphasizes that the problem arises from the act of omitting data points.

on account of lacking data

Uses "on account of" as a substitute for "due to", indicating a cause-and-effect relationship.

consequence of data scarcity

Highlights the limited amount of available data as the primary reason.

because data is absent

A more direct and simple phrasing, focusing on the state of the data.

resulting from data non-existence

Emphasizes that the data doesn't exist at all.

FAQs

How can I rephrase "due to missing data" in academic writing?

In academic writing, you can use phrases like "owing to incomplete data", "as a result of data unavailability", or "attributable to data gaps" to convey the same meaning with a slightly more formal tone.

Is it always necessary to explain why data is missing?

While not always mandatory, briefly explaining why data is missing can enhance the transparency and credibility of your research. For instance, you might mention issues with data collection or participant attrition. However, avoid speculation and focus on factual explanations.

What are the statistical implications of "due to missing data"?

Missing data can lead to biased results, reduced statistical power, and inaccurate conclusions. Depending on the pattern and extent of missingness, different statistical methods, such as imputation or complete case analysis, may be appropriate to address these issues.

How do I decide whether to exclude data "due to missing data" or use imputation methods?

The decision depends on the amount and pattern of missing data. If data is missing completely at random (MCAR) and the proportion is small, complete case analysis (excluding data) may be acceptable. However, if data is not MCAR or the proportion is substantial, imputation methods are generally preferred to minimize bias.