multilevel data

USAGE SUMMARY

The phrase "multilevel data" is correct and usable in written English.
It can be used in contexts where data is organized or analyzed at multiple levels or layers, such as in statistics, research, or data analysis. Example: "The study utilized multilevel data to assess the impact of socioeconomic factors on educational outcomes across different regions."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

For multilevel data, the resulting model is called the multilevel sequential binary logit model (MBL).

Journal of Modern Transportation

The memory devices can be used for multilevel data storage even under harsh conditions (85°C).

Nanoscale Research Letters

It offers a novel design strategy for solution processable multilevel data storage.

Organic Electronics

Hierarchical modelling is a statistical technique that allows multilevel data structure to be properly specified and estimated.

Procedia - Social and Behavioral Sciences

The U.S. company today announced that its data center in Singapore, which opened its doors just 18 months ago, will be extended with the addition of a "a second, larger, multilevel data center" right next door.

TechCrunch

Through the use of multilevel data, it examines whether significant differences in the relationship exist among people of different age groups or from different regions.

The Journal of Chinese Sociology

Some recent approaches for processing and interpreting sensor data are based on symbolic information processing, and generally, on multilevel data processing [35 37].

EURASIP Journal on Embedded Systems

This phenomenon also gives rise to the concept of multilevel data storage as long as an effective control for Vth could be realized.

Nanoscale Research Letters

Formulate a research question that addresses the multilevel data structure; Check preconditions, familiarize yourself with the variables of interest; Generate graphs and perform correlation analysis; Interpret results.

Large-scale Assessments in Education

We are aware that we are dealing with multilevel data since we deal with two level of analysis: the individual level (inventors) and the organisation level (assignees).

Triple Helix

The instrument will be built on new and mature detector technologies such as silicon strip detectors, low-power low-noise LSI, and a multilevel data acquisition system.

Advances in Space Research

Expert writing Tips

Best practice

When analyzing "multilevel data", clearly define each level of analysis and justify its relevance to your research question.

Common error

A common mistake is to analyze "multilevel data" as if it were a single-level dataset. This can lead to inaccurate conclusions due to failure to account for correlations within groups.

Linguistic Context

The phrase "multilevel data" functions as a noun phrase, often acting as the subject or object of a sentence. It commonly identifies data organized or analyzed at multiple levels, as shown by Ludwig AI.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Encyclopedias

0%

Ludwig's WRAP-UP

In summary, "multilevel data" is a noun phrase used to describe data structured across multiple levels. Ludwig AI confirms it's grammatically correct and very common, primarily appearing in scientific contexts. When working with "multilevel data", it's crucial to employ appropriate statistical methods, such as hierarchical linear modeling, to avoid misinterpreting the relationships within the data. Consider using alternatives like "hierarchical data" or "nested data" to add precision to your communication.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

Multi-level datasets

A direct synonym, simply pluralizing "dataset" to reflect multiple instances.

Hierarchical data

Focuses on the nested structure of the data, emphasizing the levels as a hierarchy.

Nested data

Highlights the containment aspect of data within different levels or groups.

Data with hierarchical structure

Explicitly states the characteristic of the data possessing a hierarchical structure.

Multilayered data

Emphasizes the presence of distinct layers within the dataset.

Tiered data structure

Highlights the arrangement of data in distinct tiers or levels.

Complex data structures

Indicates data organization is intricate, often involving multiple levels.

Grouped data

Focuses on data clustered or organized into different groups or levels.

Clustered data

Highlights the presence of natural clusters or groups within the data.

Stratified data

Emphasizes that data is divided into strata or layers, often for analysis.

FAQs

How do I analyze "multilevel data"?

Analyze "multilevel data" using statistical techniques such as hierarchical linear modeling or mixed-effects models, which account for the nested structure of the data.

What are some alternatives to "multilevel data"?

You can use alternatives like "hierarchical data" or "nested data", depending on the specific context and the aspect you want to emphasize.

Why is it important to use appropriate methods for "multilevel data"?

Using methods designed for single-level data on "multilevel data" can lead to inaccurate standard errors and biased estimates because it ignores the correlation between observations within the same group or level.

What kind of research benefits from analyzing "multilevel data"?

Research in various fields such as education, healthcare, and social sciences benefits from analyzing "multilevel data", as it allows researchers to examine the influence of factors at multiple levels (e.g., individual, group, and community) on outcomes.