discarded missing data

USAGE SUMMARY

The phrase "discarded missing data" is correct and usable in written English.
It can be used in contexts related to data analysis, statistics, or research when referring to data that has been removed due to being incomplete or unavailable. Example: "In our study, we found that the discarded missing data did not significantly affect the overall results."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

1 human-written examples

When a "V" spot signal was too weak (vector signal < 3× vector local background), the data of the corresponding cDNA clone was discarded (missing data).

BMC Genomics

Human-verified similar examples from authoritative sources

Similar Expressions

59 human-written examples

Most importantly, subjects with incomplete data are not discarded and missing data are not replaced with unprincipled estimated values or observations carried forward [ 77].

BMC Psychiatry

Sixteen surveys were discarded because of missing data.

BMC Health Services Research

First, we discarded clones with missing data in more than 5% of the arrays and applied a base-2 logaritransformationmatoon thethexpressionon data.

Genomics, Proteomics and Bioinformatics

For application in PopPK analyses performed using nonlinear mixed-effects modeling with NONMEM, we identified five methods for handling missing categorical data, which are presented in Table  I: discarding subjects with missing data (DROP), estimation of an additional covariate effect for the missing group (EXTRA), and several methods using mixture models (MIX).

AAPS Journal

Focusing our attention on those individuals working at the time of the interview, and discarding observations with missing data for any of the relevant variables, results in a sample of 14,544 observations for the whole period considered for Denmark, of which 51.2% are males, and 48.8% are females.

IZA Journal of Labor Policy

We did not use the traditional 2-stage least-squares procedure (11), because this method discards persons with missing data on X, whereas the Wald method can include such persons in the reduced-form regression.

American Journal of Epidemiology

Finally, allergens with >50% missing data were discarded and results were recorded in microarray units corresponding to the Tukey mean of corrected fluorescence intensity of replicates.

Plosone

Trials with >20% missing data were discarded from the analyses.

Cerebral Cortex

Missing data were also calculated and variables with more than 10%% missing data were discarded.

BMC Geriatrics

Any subwindow with >20% missing data was discarded, and we only considered those 300-kb windows with all 15 subwindows.

Genome Biology and Evolution

Expert writing Tips

Best practice

When documenting your data cleaning process, clearly state the criteria used for determining what constitutes "missing data" and why the decision was made to discard it. This enhances transparency and reproducibility.

Common error

Before discarding "missing data", consider whether imputation techniques or other methods might preserve valuable information and reduce bias. Discarding data should be a last resort.

Linguistic Context

The phrase "discarded missing data" functions as a descriptive term within data analysis and statistics. It indicates a specific action taken on a dataset: the removal of incomplete entries. As Ludwig AI explains, it is correct and usable in written English, particularly in scientific contexts.

Expression frequency: Rare

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Academia

0%

Ludwig's WRAP-UP

In summary, "discarded missing data" is a grammatically correct phrase used in data analysis to describe the removal of incomplete data points. According to Ludwig AI, the phrase is appropriate and usable in written English, particularly in scientific contexts. While relatively rare in general usage, it is commonly found in scientific literature. When using this phrase, it's important to be transparent about the criteria for defining "missing data" and the rationale behind discarding it, as this decision can impact the validity of your results. Consider alternative methods for handling missing data before resorting to discarding it. Remember that you can use alternative phrases like "removed incomplete data", or "excluded missing information".

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

removed incomplete data

Replaces "discarded" with "removed" and "missing" with "incomplete", maintaining the core meaning but with slightly different vocabulary.

excluded missing information

Substitutes "data" with "information" and "discarded" with "excluded", offering a more formal tone.

omitted incomplete data

Uses "omitted" in place of "discarded", suggesting a deliberate leaving out of the data.

rejected missing values

Replaces "data" with "values" and "discarded" with "rejected", implying a stronger dismissal of the data.

ignored missing data points

Uses "ignored" instead of "discarded", suggesting the data was not considered in the analysis.

eliminated absent data

Replaces "missing" with "absent" and "discarded" with "eliminated", emphasizing the removal of the data.

deleted missing records

Substitutes "data" with "records" and "discarded" with "deleted", implying a permanent removal of the data.

disregarded incomplete observations

Replaces "data" with "observations", offering a different perspective on the data's nature and using "disregarded" instead of "discarded".

filtered out missing entries

Uses "filtered out" instead of "discarded", emphasizing the process of selectively removing the data.

suppressed missing data instances

Substitutes "discarded" with "suppressed", suggesting that the data was hidden or prevented from affecting the analysis.

FAQs

When is it appropriate to use the phrase "discarded missing data"?

The phrase "discarded missing data" is appropriate when describing a process where incomplete or unavailable data points were intentionally removed from a dataset prior to analysis. This is often done to avoid skewing results or violating assumptions of statistical tests.

What are some alternatives to saying "discarded missing data"?

You can use alternatives like "removed incomplete data", "excluded missing information", or "omitted incomplete data" depending on the context.

What are the implications of using "discarded missing data" in a research study?

Discarding "missing data" can lead to a loss of statistical power and potentially introduce bias if the missing data is not completely random. It's crucial to justify this decision and consider alternative methods for handling missingness.

Is there a difference between "discarded missing data" and imputing missing data?

"Discarded missing data" means removing the data points entirely, while imputation involves replacing the missing values with estimated values based on other available information. Imputation aims to preserve the sample size and potentially reduce bias, but it introduces its own set of assumptions and potential errors.