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Confidence Coefficient

Confidence Coefficient

The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under both the...

Interpretation of Confidence Intervals

Interpretation of Confidence Intervals

A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
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Sample Size Calculation

Sample Size Calculation

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Confidence Intervals

Confidence Intervals

An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a sample proportion. However, unlike the point estimate which is a single value, the confidence interval contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
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Related Experiment Video

Updated: May 20, 2026

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

Sample size formulas for estimating intraclass correlation coefficients with precision and assurance.

¹Department of Epidemiology and Biostatistics and Robarts Clinical Trials of Robarts Research Institute, Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada. gzou@robarts.ca

Statistics in Medicine

|July 6, 2012

Summary

Determining sample size for reliability studies needs a new approach. This study introduces a method ensuring a specific probability of achieving desired confidence interval width for accurate intraclass correlation coefficient estimation.

Related Experiment Videos

Last Updated: May 20, 2026

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

Area of Science:

Biostatistics
Psychometrics
Medical Statistics

Background:

Sample size determination for intraclass correlation coefficient (ICC) estimation typically relies on achieving a desired confidence interval width.
This traditional method may lead to inadequate sample sizes due to neglecting the probability of attaining the specified precision.

Purpose of the Study:

To present a novel method for sample size calculation in reliability studies.
To explicitly incorporate the probability of achieving a prespecified confidence interval width or lower limit for ICC estimation.

Main Methods:

Development of closed-form formulas for sample size calculation.
Incorporation of a prespecified probability for achieving the desired confidence interval precision.

Main Results:

The proposed method provides a more reliable approach to sample size determination.
The derived formulas are demonstrated to be highly accurate in practice.

Conclusions:

The new method enhances the precision of sample size planning in reliability studies.
This approach offers a statistically sounder basis for ensuring adequate study power and reliable ICC estimates.