clustered data

USAGE SUMMARY

"clustered data" is correct and usable in written English.
You can use this phrase when talking about a set of data points that are grouped together in some meaningful way. For example, "The data scientist was able to make sense of the clustered data to draw meaningful conclusions from the information."

✓ Grammatically correct

Science

Academia

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Therefore, all analyses are design-based, taking the clustered data structure into account, using Stata's [ 62] procedures for clustered data [ 63].

BMC Psychiatry

Appropriate statistical analyses for clustered data must be adopted.

Journal of Science and Medicine in Sport

This situation is referred to as clustered data.

Computational Statistics & Data Analysis

Her statistical interests center around neurostatistics, time series analysis, and methods for longitudinal or clustered data.

Stanford University

Jiang, Y., Lee, M. T. & Rosner, B. Wilcoxon rank-based tests for clustered data with R package clusrank (2017).

Nature

The redundant clustered data points in clusters are thus removed to speed up SVM training process.

Neurocomputing

Locally efficient estimators are implemented for longitudinal data with continuous outcomes and clustered data with binary outcomes.

Harvard University

We will focus on specific versions of these tools for the most common forms of longitudinal and clustered data.

Harvard University

This paper works through the sample size calculations for clustered data.

Statistics & Probability Letters

Multilevel and hierarchical models for longitudinal and/or clustered data.

Duke University

Dictionaries are designed for a set of clustered data.

EURASIP Journal on Image and Video Processing

Expert writing Tips

Best practice

When analyzing "clustered data", always account for the intra-cluster correlation to avoid underestimating standard errors and drawing incorrect conclusions.

Common error

A common mistake is to treat "clustered data" as independent observations. This leads to artificially small standard errors and inflated significance levels. Use statistical methods appropriate for clustered data, such as mixed-effects models or generalized estimating equations.

Linguistic Context

The phrase "clustered data" functions primarily as a noun phrase. It identifies a specific type of dataset characterized by grouped observations. Ludwig shows that this phrase is often used in the context of statistical analysis and research methodologies.

Expression frequency: Very common

Frequent in

Science

55%

Academia

35%

News & Media

10%

Less common in

Formal & Business

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, "clustered data" is a noun phrase referring to datasets where observations are grouped, requiring specific statistical methods. As confirmed by Ludwig, it’s grammatically correct and commonly used, predominantly in scientific and academic fields. The primary purpose is to describe and categorize datasets with a specific structure, influencing analytical approaches. Remember to use appropriate statistical methods to account for intra-cluster correlation and avoid misinterpretations. Consider alternatives like "grouped data" or "hierarchical data" depending on the context. The high frequency and authoritative sources indicate its importance in research and data analysis.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

grouped data

Focuses on the act of grouping rather than the resulting structure, suggesting a process-oriented view.

correlated data

Emphasizes the statistical dependency between data points within the clusters.

hierarchical data

Highlights the nested structure within the data, implying a multi-level arrangement.

multilevel data

Similar to hierarchical data, but specifically refers to data organized at multiple levels.

nested data

Describes data where one set of observations is contained within another.

aggregated data

Implies that data has been combined or summarized within each cluster.

dependent data

General term for data points that are not independent of each other.

structured data

Broad term indicating that the data has an organized format, which can include clustering.

cohesive data

Focuses on the internal consistency and relatedness within the clusters.

interrelated data

Emphasizes the connections and relationships between data points within the clusters.

FAQs

How should I analyze "clustered data"?

Use statistical methods that account for the correlation within clusters, such as mixed-effects models, generalized estimating equations (GEE), or hierarchical linear models. Ignoring the clustering structure can lead to incorrect statistical inferences.

What does "clustered data" mean?

"Clustered data" refers to data where observations are grouped into clusters, and observations within the same cluster are more similar to each other than observations in different clusters. Examples include students within schools, patients within hospitals, or repeated measures within individuals.

Why is it important to account for clustering in data analysis?

Failing to account for clustering leads to underestimated standard errors, inflated Type I error rates, and potentially incorrect conclusions. Appropriate statistical methods are needed to address the non-independence of observations within clusters.

What are some alternatives to "clustered data"?

Depending on the context, you can use alternatives like "grouped data", "hierarchical data", or "multilevel data".