Related Experiment Video
Updated: Apr 29, 2026

Measurement of Fronto-limbic Activity Using an Emotional Oddball Task in Children with Familial High Risk for Schizophrenia
Published on: December 2, 2015
Intracluster correlation coefficient in multicenter childhood trauma studies
Bahman Roudsari1, Raymond Fowler, Avery Nathens
1University of Texas School of Public Health, Dallas Regional Campus, Dallas, Texas 75390-9128, USA. bahman.roudsari@utsouthwestern.edu
Insights
Intracluster correlation coefficients (ICCs) were calculated for childhood trauma outcomes. These ICCs are crucial for accurately powering future cluster randomized trials in pediatric trauma research.
Area of Science:
- Trauma research
- Pediatric critical care
- Biostatistics
Background:
- Multicenter childhood injury studies require accurate statistical power calculations.
- Intracluster correlation coefficients (ICCs) are essential for cluster randomized trials but vary by outcome and population.
- Previous ICC values for pediatric trauma outcomes were not well-established.
Purpose of the Study:
- To calculate the intracluster correlation coefficient (ICC) for emergency department (ED) shock rate, early trauma death, and in-hospital trauma death rate in multicenter childhood injuries.
- To provide data for sample size calculations in pediatric trauma research.
Main Methods:
- Utilized the National Trauma Data Bank (5th revision), a large US multicenter trauma registry.
- Calculated ICCs for in-hospital trauma death rate using data from 80 trauma centers.
- Calculated ICCs for ED shock and early trauma death rates using data from 33 states.
Main Results:
- Analyzed data from 952,242 patients (2000-2004), with 13% under 15 years old.
- Calculated ICCs: 0.005 for ED shock rate, 0.014 for early trauma death, and 0.023 for in-hospital death.
- ICCs were stratified by sex and injury type (blunt vs. penetrating).
Conclusions:
- The calculated ICCs are vital for sample size determination in clustered childhood trauma studies.
- Failure to adjust for ICCs in cluster randomized trials can lead to significant underpowering.
- These findings will improve the design and reliability of pediatric trauma research.
Objective:
To calculate the intracluster correlation coefficient (ICC) for emergency department (ED) shock rate, early trauma death (ie, death during the first 24 h after arrival at hospital), and in-hospital trauma death rate for multicenter childhood injuries.
Methods:
The National Trauma Data Bank (5th revision), the largest multicenter trauma registry in the US, was used. Data from 80 trauma centers were used to calculate the ICC for in-hospital trauma death rate. Thirty three states provided data for calculation of the ICC for ED shock and early trauma death rate.
Results:
From 2000 to 2004, 13% of the 952 242 patients in the National Trauma Data Bank were <15 years old. Approximately 17 000 of these children had injuries with an injury severity score >15, of whom 84% (14 095 subjects) were hospitalized at 80 level I or II trauma centers in 33 states. The ICCs for ED shock rate, early trauma death rate, and in-hospital death rate were 0.005 (95% CI 0.000 to 0.010), 0.014 (95% CI 0.004 to 0.024), and 0.023 (95% CI 0.013 to 0.033), respectively. These ICCs were calculated for boys and girls and also for blunt and penetrating injuries.
Conclusion:
Clustered childhood trauma studies that aim to compare different aspects of pre-hospital and hospital trauma care should incorporate these ICCs for sample calculation. When cluster randomized clinical trials are mounted, if sample sizes are calculated without adjustment for ICC, then the planned trial is likely to be seriously underpowered.
Related Concept Videos
Correlations
Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Coefficient of Correlation
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
Spearman's Rank Correlation Test
Spearman's test calculates correlation by...
Confounding in Epidemiological Studies
Kendall's Coefficient of Concordance

