reliability coefficient

USAGE SUMMARY

The phrase "reliability coefficient" is correct and usable in written English.
It is typically used in statistics and research to refer to a measure of the consistency or stability of a test or measurement instrument. Example: "The reliability coefficient of the survey was calculated to ensure that the results were consistent across different samples."

✓ Grammatically correct

Science

Academia

Formal & Business

News & Media

Human-verified examples from authoritative sources

Exact Expressions

60 human-written examples

The questionnaire is reliable (reliability coefficient α = .91) [ 19, 29].

BMC Psychiatry

The Chronbach's alpha reliability coefficient of the tool was 0.826.

Surgery

The overall reliability coefficient for the scale is 0.96.

Procedia - Social and Behavioral Sciences

Using a three-week time spread between the first and second test, we then examined the pairs of questionnaires, and the reliability coefficient indicated no significant variation.

Harvard Business Review

Reliability coefficient.

International Journal of Educational Technology in Higher Education

McDonald's ω (reliability coefficient).

Large-scale Assessments in Education

Composite reliability coefficient.

Frontiers of Business Research in China

The test-retest reliability coefficient was 98.6%.

Duke University

The test retest reliability coefficient was 0.97.

Journal of Orthopaedics and Traumatology

The reliability coefficient was calculated using Cronbach's alpha.

International Journal of Emergency Medicine

The Spearman-Brown split-half reliability coefficient was.70.70

Empirical Research in Vocational Education and Training

Expert writing Tips

Best practice

When reporting a "reliability coefficient", always specify the type of reliability being assessed (e.g., Cronbach's alpha, test-retest reliability, inter-rater reliability) to provide clarity and context.

Common error

Avoid assuming a higher "reliability coefficient" automatically implies a better measurement tool. Consider the context, the purpose of the measurement, and the potential trade-offs between reliability and validity.

Linguistic Context

The phrase "reliability coefficient" functions as a noun phrase that identifies a specific statistical measure. As Ludwig AI confirms, it is a standard term in research and statistics. It serves to name a quantifiable index of measurement consistency.

Expression frequency: Very common

Frequent in

Science

78%

Academia

13%

Formal & Business

3%

Less common in

News & Media

3%

Encyclopedias

0%

Wiki

0%

Ludwig's WRAP-UP

The phrase "reliability coefficient" is a well-established term in statistics and research, used to express the consistency and stability of a measurement. As Ludwig AI confirms, it's grammatically correct and suitable for use in formal, scientific, and professional contexts. It is most commonly found in scientific and academic publications. Related phrases include "consistency index" and "stability measure". When using this phrase, remember to specify the type of reliability being assessed (e.g., Cronbach's alpha) and avoid overstating the implications of a high coefficient.

More alternative expressions

Phrases that express similar concepts, ordered by semantic similarity:

test-retest reliability

Specifically assesses the stability of a measure over two points in time.

consistency index

Focuses on the consistency of results rather than explicitly quantifying reliability.

internal consistency

Refers to how well the items within a test measure the same construct.

stability measure

Highlights the stability of a measurement over time.

reproducibility score

Highlights the ability to reproduce the same results under similar conditions.

precision metric

Emphasizes the accuracy and exactness of a measurement.

agreement level

Focuses on the extent to which different measurements or raters agree.

accuracy rate

Refers to the proportion of correct or accurate measurements.

dependability factor

Indicates the degree to which a measurement can be relied upon.

concordance statistic

A statistical measure of agreement between two or more measurements.

FAQs

How is the "reliability coefficient" calculated?

The calculation of the "reliability coefficient" varies depending on the type of reliability being assessed. Common methods include Cronbach's alpha for internal consistency, Pearson correlation for test-retest reliability, and intraclass correlation (ICC) for inter-rater reliability. Each method uses a specific formula to quantify the consistency or stability of the measurements.

What is a good value for a "reliability coefficient"?

Generally, a "reliability coefficient" of 0.70 or higher is considered acceptable for group-level comparisons, while a coefficient of 0.90 or higher is recommended for individual-level decisions. However, the specific threshold may vary depending on the context and the stakes involved. See also "acceptable reliability".

What factors can affect the "reliability coefficient"?

Several factors can influence the "reliability coefficient", including the sample size, the heterogeneity of the sample, the length of the measurement instrument, and the presence of systematic or random errors. Larger sample sizes and more homogeneous samples tend to produce higher reliability coefficients.

Can a test be valid without being reliable, or reliable without being valid?

A test can be reliable without being valid. Reliability is a necessary but not sufficient condition for validity. A test can consistently measure something (reliable) but not measure what it is intended to measure (not valid). However, a test cannot be valid without being reliable because if a test is not consistent, it cannot accurately measure the construct of interest.