univariable analysis

USAGE SUMMARY

'univariable analysis' is correct and can be used in written English.
It refers to the analysis of one variable (either qualitative or quantitative) at a time and it is commonly used in statistical analysis. For example, "A univariable analysis showed that there was a statistically significant difference between the two groups."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Univariable analysis was performed on ICU- and 90-day mortality.

Annals of Intensive Care

T-Student and χ2 (p < 0.05) were used for the univariable analysis.

Intensive Care Medicine Experimental

We performed univariable analysis of the risk factors identified in the original LIPS study.

Annals of Intensive Care

Univariable analysis first assessed the association between each variable and ESBL-PE ICUAP.

Annals of Intensive Care

Our study found an association with ARDS in univariable analysis, but our multivariable analysis did not.

Annals of Intensive Care

We used T-Student and χ2 (p < 0.05) for univariable analysis.

Intensive Care Medicine Experimental

Variables were screened using a univariable analysis and logistic multiple-regression models were developed in a forward-selection process.

Preventive Veterinary Medicine

By univariable analysis, factors associated with mortality included age, platelet count, status epilepticus, troponin level, cardiac arrest.

Annals of Intensive Care

Univariable analysis was performed to explore association with ICU lenght of stay (ILOS) and UCI vital outcome.

Intensive Care Medicine Experimental

Results of the univariable analysis of factors associated with ICU mortality are provided in Additional file 1: Table S2.

Annals of Intensive Care

Table S1 Univariable analysis of factors associated with in-hospital mortality in patients without ARDS receiving mechanical ventilation.

Annals of Intensive Care

Expert writing Tips

Best practice

Always follow up a "univariable analysis" with a multivariable analysis to control for confounding variables and assess the independent effect of each variable.

Common error

Do not interpret significant associations from a "univariable analysis" as causal relationships. "Univariable analysis" only identifies potential associations, not causation. Further investigation is needed to establish causality.

Linguistic Context

The phrase "univariable analysis" functions as a noun phrase, typically used to describe a specific type of statistical analysis. As Ludwig AI confirms, it's grammatically correct and frequently used. Examples show its application in scientific research to assess relationships between individual variables and outcomes.

Expression frequency: Very common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Ludwig's WRAP-UP

In summary, "univariable analysis" is a grammatically sound and very common term used in scientific research to describe the process of analyzing one variable at a time. As Ludwig AI points out, the phrase is correct and suitable for use in formal writing, particularly in the sciences. Best practices include specifying the statistical tests used and following up with multivariable analysis. Common errors involve assuming causation based solely on "univariable analysis" results. This initial exploratory step is crucial for identifying significant variables before further investigation.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

single variable analysis

This alternative directly replaces "univariable" with "single variable", simplifying the terminology while retaining the core meaning.

univariate analysis

This is a very common synonym, using a different prefix to convey the same meaning of analyzing a single variable.

single factor analysis

This alternative emphasizes the 'factor' aspect, which is suitable when considering variables as factors influencing an outcome.

one-variable analysis

This alternative uses a numerical prefix to emphasize the singularity of the variable being analyzed.

analysis of a single variable

This rephrasing expands on the term, making it more explicit about what is being analyzed.

examining individual variable effects

This phrase shifts from naming the analysis to describing its action and focus, emphasizing the examination of effects.

assessing each variable independently

This describes the process of "univariable analysis", focusing on independent assessment.

analyzing one variable at a time

This emphasizes the sequential and singular nature of the analysis.

isolated variable analysis

This highlights the isolation of the variable being analyzed from other potential influences.

analysis by individual variable

This rephrasing specifies that the analysis is conducted on a variable-by-variable basis.

FAQs

What is the purpose of performing a "univariable analysis"?

The primary purpose of a "univariable analysis" is to examine the distribution and characteristics of a single variable. It helps in understanding the basic properties of the variable, such as central tendency, dispersion, and shape, before conducting more complex analyses.

When should I use "univariable analysis" versus multivariable analysis?

"Univariable analysis" is typically used as an initial step to explore individual variables and identify potential associations. Multivariable analysis, on the other hand, is used to examine the relationships between multiple variables simultaneously while controlling for confounding factors. Typically, you would follow a "univariable analysis" with multivariable methods.

What statistical tests are commonly used in "univariable analysis"?

Common statistical tests used in "univariable analysis" include t-tests for comparing means, chi-squared tests for categorical variables, ANOVA for comparing means across multiple groups, and correlation analysis for assessing the relationship between two continuous variables.

How do I interpret the results of a "univariable analysis"?

Interpreting a "univariable analysis" involves examining descriptive statistics (e.g., mean, median, standard deviation) and statistical significance (p-values). A significant p-value suggests that the variable is associated with the outcome of interest, but further analysis is needed to determine the nature and strength of the relationship.