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Confidence Intervals

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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: Jun 26, 2026

High-throughput Quantitative Real-time RT-PCR Assay for Determining Expression Profiles of Types I and III Interferon Subtypes

High-throughput Quantitative Real-time RT-PCR Assay for Determining Expression Profiles of Types I and III Interferon Subtypes

Published on: March 24, 2015

Reference intervals: the way forward.

Ferruccio Ceriotti¹, Rolf Hinzmann, Mauro Panteghini

¹Diagnostica e Ricerca San Raffaele S.p.A, Milan, Italy. ceriotti.ferruccio@hsr.it

Annals of Clinical Biochemistry

|December 24, 2008

Summary

This summary is machine-generated.

This review updates knowledge on biological reference intervals, emphasizing updated standards and new statistical methods for defining reliable reference limits. It explores creating common intervals across laboratories for improved consistency.

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Area of Science:

Clinical Chemistry
Medical Diagnostics
Laboratory Medicine

Background:

Growing regulatory demands from International Organization for Standardization (ISO) 15189 and EU in vitro diagnostic medical devices directives necessitate periodic review and detailed information on biological reference intervals.
Existing approaches for defining reference intervals require updates to address current scientific and regulatory landscapes.

Purpose of the Study:

To provide an updated review on the theoretical aspects and critical issues concerning biological reference intervals.
To discuss limitations of current data mining techniques for reference data acquisition.
To explore new statistical methods and standardization concepts for defining common, transferable reference intervals.

Main Methods:

Review of existing literature and guidelines on reference interval determination.
Analysis of theoretical approaches and statistical methodologies.
Discussion of standardization concepts, including traceability and common reference intervals.

Main Results:

The fundamental approach to defining reference intervals remains valid, but data mining from existing databases has significant limitations.
New statistical methods for outlier detection and reference limit computation are recommended.
Improved standardization and traceability offer potential for developing common reference intervals applicable across multiple laboratories.

Conclusions:

Periodic review and updated methodologies are crucial for biological reference intervals.
New statistical approaches and standardization initiatives are key to overcoming limitations in current reference interval practices.
Developing common reference intervals can reduce unwarranted variability between laboratories, enhancing diagnostic consistency.