matching factor

USAGE SUMMARY

The phrase "matching factor" is correct and usable in written English.
It can be used in contexts where you are discussing elements that correspond or align with each other in some way, such as in data analysis or comparisons. Example: "The matching factor between the two datasets indicates a strong correlation in their results."

✓ Grammatically correct

Science

Human-verified examples from authoritative sources

Exact Expressions

19 human-written examples

With matching factor of AVT of around 1.2 mV.μm, SOI FinFETs are resilient to statistical variability as well.

Silicon-On-Insulator (SOI) Technology Manufacture and Applications

In order to facilitate the application of this concept, we developed a computer program which provides estimates of power and efficiency varying the proportion of the matching factor in controls over all possible values from 1 to 99%.

Computer Methods and Programs in Biomedicine

The program allows one to estimate the effect of frequency matching on power and efficiency to study multiplicative interactions and to assess the optimal prevalence of the matching factor in selected controls for a given scenario which often differs from the prevalence in cases (aimed at in traditional 'fixed' frequency matching).

Computer Methods and Programs in Biomedicine

AMDIS parameters were: 60% minimum matching factor, threshold-low, resolution-medium, sensitivity-high, shape requirements-medium, adjacent peak subtraction-two, low m/z 50, high m/z 300.

Plosone

bUnconditional haplotype analysis adjusted for matching factor year of birth.

Breast Cancer Research

All statistical models were adjusted for the frequency matching factor, 5-year age group.

Environmental Health: A Global Access Science Source

Human-verified similar examples from authoritative sources

Similar Expressions

41 human-written examples

Conditional and unconditional logistic regression adjusting for matching factors and multivariate covariates were used to estimate the relative risk (RR) and results were similar.

Plosone

Because results remained virtually unchanged regardless of the model used, we present results from the conditional models adjusting for matching factors only.

Plosone

*Adjusted for matching factors only.

British Medical Journal

*Model based on matching factors only.

British Medical Journal

The distribution of matching factors for this nested case control study is detailed in Table S1.

Cancer Medicine

Expert writing Tips

Best practice

When using "matching factor" in statistical analysis, clearly define what variables are being matched and why. For example, specify "age" or "location" as a matching factor to enhance clarity.

Common error

Avoid assuming that a high "matching factor" automatically implies causation. Correlation does not equal causation; further analysis is needed to establish causality between matched variables.

Linguistic Context

The phrase "matching factor" functions primarily as a noun phrase identifying a specific element used for comparison or control in research or analysis. Ludwig AI confirms this usage through its examples, where it's often used to describe variables like age or location.

Expression frequency: Common

Frequent in

Science

100%

Less common in

News & Media

0%

Formal & Business

0%

Science

0%

Ludwig's WRAP-UP

The phrase "matching factor" is commonly employed in scientific and technical fields to denote a variable used for aligning or comparing groups or datasets. As Ludwig AI indicates, it's crucial for controlling confounding influences in research. This analysis highlights that "matching factor" is grammatically correct and primarily used in formal, scientific contexts. When using this phrase, ensure clarity in defining the variables being matched and be cautious about inferring causation solely from matched data. While the frequency of use is common, its application remains specific to research and analytical environments.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

correlation coefficient

Focuses specifically on the statistical measure of the linear relationship between two variables.

alignment metric

Emphasizes the measurement of how well two or more things align or correspond.

agreement index

Highlights the degree to which different sources or methods yield consistent results.

correspondence measure

Indicates the extent to which two things are in agreement or similarity.

similarity indicator

Points to something that reveals how alike two or more things are.

compatibility criterion

Emphasizes the conditions under which two or more things can coexist or work together effectively.

equivalence parameter

Focuses on parameters that indicate equality or interchangeability.

consistency variable

Highlights a variable that shows a consistent pattern or relationship.

harmonization element

Indicates a component that brings different elements into agreement or unity.

congruence attribute

Emphasizes the quality of being in agreement or harmony.

FAQs

How is "matching factor" used in research studies?

In research, the "matching factor" is a variable used to pair subjects in different groups to control for potential confounding influences. This ensures groups are similar in key aspects, like age or gender, allowing for a more accurate comparison of the variable being studied.

What does adjusting for a "matching factor" mean?

Adjusting for a "matching factor" means accounting for the influence of that variable in statistical analysis. This helps to remove the effects of the matching factor on the outcome, providing a clearer picture of the relationship between other variables of interest.

Which variables are commonly used as a "matching factor"?

Common "matching factors" include age, gender, ethnicity, socioeconomic status, and geographic location. These variables are often used because they can significantly impact the outcomes of many studies, and /s/controlling+for them helps to reduce bias.

What are the limitations of using "matching factor" in study design?

While "matching factor" helps control for confounding, over-matching can inadvertently remove real effects or introduce bias. It's also important to ensure that the matching factors are relevant and justified to avoid distorting the study's findings. Another limitation is the lost opportunity to study the association between the outcome and the /s/matched+factors themselves.