multiple comparisons

USAGE SUMMARY

The phrase "multiple comparisons" is a valid and commonly used phrase in written English.
This phrase is typically used to refer to a statistical analysis or research method in which multiple independent variables are compared. For example: "In order to make an accurate assessment, the researchers used multiple comparisons to draw a conclusion about the effects of the experiment."

✓ Grammatically correct

Science

Academia

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

Multiple comparisons.

Stanford University

No corrections were made for multiple comparisons.

Nature

Dunn, O. J. Multiple comparisons among means.

Nature

No correction for multiple comparisons was applied.

Nature

For multiple comparisons, Bonferroni corrections were used.

Nature

Statistics included correction for multiple comparisons.

Stanford University

Results are FWE-corrected for multiple comparisons (p = 0.05).

Nature

We controlled for multiple comparisons using surrogate-based cluster statistics30.

Nature

Bonferroni's correction was used for post-hoc multiple comparisons.

Nature

Multiple comparisons among levels were checked with Tukey posthoc tests.

Nature

Correction for multiple comparisons was applied.

Journal of Psychiatric Research

Expert writing Tips

Best practice

When performing "multiple comparisons", always specify the method used to control for the familywise error rate (e.g., Bonferroni correction, Tukey's test).

Common error

A common mistake is to perform "multiple comparisons" without adjusting the significance level, which can lead to an increased risk of Type I errors (false positives). Always apply a correction method to maintain the desired alpha level.

Linguistic Context

The phrase "multiple comparisons" functions as a noun phrase that refers to the act of performing several statistical tests or comparisons within a single study or experiment. Ludwig AI confirms its validity in academic and scientific writing.

Expression frequency: Very common

Frequent in

Science

75%

Academia

25%

News & Media

0%

Less common in

Formal & Business

0%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

In summary, the phrase "multiple comparisons" is a common and grammatically sound term used primarily in scientific and academic writing. As Ludwig AI confirms, it denotes the practice of making several statistical comparisons simultaneously. A key consideration when using this phrase is the understanding of statistical corrections needed to account for the increased risk of Type I errors. Common alternative phrases include "multiple contrasts", "various comparisons", and "post-hoc analysis". Neglecting to adjust for multiplicity is a frequent error. The phrase is most frequently encountered in scientific publications and academic research papers.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

multiple contrasts

Focuses on the specific statistical tests performed after ANOVA to compare group means.

various comparisons

Emphasizes the diversity of comparisons being made, suitable when different types of data are being compared.

numerous comparisons

Highlights the quantity of comparisons, useful when there are many groups or variables being analyzed.

several comparisons

Similar to 'numerous comparisons', but may imply a more limited set of comparisons.

post-hoc analysis

Describes the analysis performed after an initial significant result (e.g., ANOVA) to determine which groups differ.

pairwise comparisons

Specifically refers to comparisons made between all possible pairs of groups.

statistical contrasts

Highlights the use of statistical methods to compare different groups or conditions.

familywise error rate control

Emphasizes the method used to adjust for the increased risk of Type I error when conducting multiple tests.

adjustment for multiplicity

Focuses on the act of correcting for the increased chance of false positives in multiple tests.

correction for multiple testing

Indicates that a method has been applied to counteract the effects of performing multiple statistical tests.

FAQs

Why is it important to correct for "multiple comparisons" in statistical analysis?

When performing many statistical tests, the chance of falsely rejecting the null hypothesis (Type I error) increases. Correcting for "multiple comparisons" controls this risk, ensuring more reliable results.

What are some common methods for correcting for "multiple comparisons"?

Common methods include Bonferroni correction, "Tukey's test", "Holm-Sidak method", "FDR correction" (Benjamini-Hochberg), and "Scheffe test". The choice depends on the specific analysis and desired level of stringency.

When should I use a more conservative correction method for "multiple comparisons"?

Use a more conservative method like Bonferroni when it is critical to minimize false positives, even at the cost of potentially missing true effects. This is often the case in exploratory research or when dealing with small sample sizes.

What happens if I don't adjust for "multiple comparisons"?

Failing to adjust for "multiple comparisons" increases the risk of making a Type I error, which can lead to incorrect conclusions and wasted resources. This is especially problematic in fields where reproducibility is crucial.