Intraclass correlation for reliability assessment: the introduction of a validated program in SAS (ICC6)

Reliability refers to how measurements can produce consistent results and are crucial for any scientific research measurement. Intraclass correlation coefficient (ICC) is the most widely used method to determine the reproducibility of measurements of various statistical techniques. Calculated ICC an...

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Bibliographic Details
Published inHealth services and outcomes research methodology Vol. 24; no. 1; pp. 1 - 13
Main Authors Senthil Kumar, V. S., Shahraz, Saeid
Format Journal Article
LanguageEnglish
Published New York Springer US 01.03.2024
Springer Nature B.V
Subjects
Confidence intervals
Correlation analysis
Economics
Health Administration
Medicine
Medicine & Public Health
Methodology of the Social Sciences
Public Health
Reliability
Reproducibility
Research methodology
Software packages
Statistics
Variance analysis
ICC
Intraclass correlation
Reliability
ANOVA
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Summary:Reliability refers to how measurements can produce consistent results and are crucial for any scientific research measurement. Intraclass correlation coefficient (ICC) is the most widely used method to determine the reproducibility of measurements of various statistical techniques. Calculated ICC and its confidence interval that reveal the underlying sampling distribution may help detect an experimental method's ability to identify systematic differences between research participants in a test. This study aimed to introduce a new SAS macro, ICC6, for calculating different ICC forms and their confidence intervals. A SAS macro that employs the PROC GLM procedure in SAS was created to generate two-way random effects (ANOVA) estimates. A simulated dataset was used to input the macro to calculate the point estimates for different ICCs. The ICC forms' upper and lower confidence interval limits were calculated using the F statistics distribution. Our SAS macro provides a complete set of various ICC forms and their confidence intervals. A validation analysis using commercial software packages STATA and SPSS delivered identical results. A development of SAS methodology using publicly available statistical approaches in estimating six distinct forms of ICC and their confidence intervals has been reported in this article. This work is an extension of general methodology supported by a few other statistical software packages to SAS.
ISSN:1387-3741
1572-9400
DOI:10.1007/s10742-023-00299-x