missing responses

USAGE SUMMARY

The phrase "missing responses" is correct and usable in written English.
It can be used to refer to replies or answers that have not been provided or are absent in a given context. Example: "We need to follow up with the team regarding the missing responses to the survey we sent out last week."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The nutritional questionnaire was first screened for missing responses and those questionnaires with more than 10 missing responses in the food and beverage section were excluded.

BMC Musculoskeletal Disorders

There were minimal missing responses on the PedsQL™ Generic Core Scales and no missing responses on the PedsQL™ Oral Health Scale.

Health and Quality of Life Outcomes

There were few missing responses to the MOS; less than 1% (1/133) of the participants had missing responses for any items.

Health and Quality of Life Outcomes

No imputation was performed for missing responses.

Journal of Patient-Reported Outcomes

Due to missing responses, the final sample comprised 254 students.

International Journal of Educational Technology in Higher Education

Missing responses for omitted items are usually not random.

Empirical Research in Vocational Education and Training

In the present paper, we extend the work to the case of missing responses.

Statistics & Probability Letters

We excluded trials with missing responses or missing confidence ratings.

Plosone

Otherwise, missing responses were considered to be negative outcomes.

Plosone

† Excluding missing responses.

BMC Pediatrics

cThree missing responses.

Arthritis Research and Therapy

Expert writing Tips

Best practice

When analyzing data with "missing responses", clearly state the method used to handle these gaps, such as exclusion, imputation, or considering them as negative outcomes. This ensures transparency and reproducibility of your results.

Common error

A common mistake is to assume that "missing responses" are randomly distributed without conducting appropriate statistical tests. Always assess whether the missing data follows a specific pattern, as non-random missingness can bias your findings.

Linguistic Context

The phrase "missing responses" functions primarily as a noun phrase, often serving as the subject or object of a sentence. It refers to the absence of answers or replies in a given context, as evidenced by Ludwig's examples where it's used to describe incomplete questionnaires, excluded trials, and data analysis challenges.

Expression frequency: Very common

Frequent in

Science

98%

Formal & Business

1%

News & Media

1%

Less common in

Encyclopedias

0%

Wiki

0%

Reference

0%

Ludwig's WRAP-UP

In summary, the term "missing responses" is a grammatically correct and frequently used noun phrase, particularly within scientific and academic domains. As Ludwig highlights through its examples, it denotes the absence of answers or replies in various contexts, often requiring specific analytical or corrective actions. While the phrase is clear and direct, alternatives like "unanswered replies" or "incomplete answers" can provide nuanced variations. When dealing with data that includes "missing responses", it's crucial to acknowledge and address them methodically to avoid potential bias and ensure reliable results.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

unanswered replies

Focuses on the replies not being answered, changing the noun from "responses" to "replies".

absent feedback

Replaces "responses" with "feedback", highlighting the lack of input or reaction.

incomplete answers

Emphasizes that the answers provided are not fully present or finished.

lack of replies

Shifts the focus to the absence of replies rather than the responses themselves.

outstanding responses

Highlights that responses are still awaited or due.

unsubmitted answers

Emphasizes that the answers were not sent or provided.

void replies

Focuses on the replies being null or empty.

blank submissions

Replaces responses with submissions, highlighting the lack of content in the submitted material.

unfilled questionnaires

Focuses on the absence of information in questionnaire forms.

data omissions

Highlights the absence of data points or information.

FAQs

How should I handle "missing responses" in a survey?

The approach to dealing with "missing responses" depends on the research question and the nature of the missing data. Common methods include excluding cases with missing data, imputing values based on other data, or treating the missing responses as a specific category.

What statistical methods can be used to address "missing responses"?

Several statistical techniques can handle "missing responses", such as multiple imputation, maximum likelihood estimation, and inverse probability weighting. The choice of method depends on whether the data is missing completely at random (MCAR), missing at random (MAR), or missing not at random (MNAR).

What does it mean if data is 'missing at random'?

When data is 'missing at random', the probability of a response being missing depends on the observed data, but not on the unobserved data itself. This assumption is crucial for using imputation techniques to handle "missing data".

How do "missing responses" affect the validity of research results?

"Missing responses" can reduce the statistical power of a study and potentially introduce bias if the missing data is not handled appropriately. This can lead to inaccurate conclusions and limit the generalizability of the findings.