Related Experiment Video
Updated: Apr 14, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Intracluster correlation coefficients for sample size calculations related to cardiovascular disease prevention and
Jatinderpreet Singh1, Clare Liddy2,3, William Hogg4,5
1Bruyère Research Institute, C.T. Lamont Primary Health Care Research Centre, 43 Bruyere St (Annex E), Ottawa, ON, K1R 7G5, Canada. jsingh@bruyere.org.
Background:
Few studies have comprehensively reported intracluster correlation coefficient (ICC) estimates for outcomes collected in primary care settings. Using data from a large primary care study, we aimed to: a) report ICCs for process-of-care and clinical outcome measures related to cardiovascular disease management and prevention, and b) investigate the impact of practice structure and rurality on ICC estimates.
Methods:
We used baseline data from the Improved Delivery of Cardiovascular Care (IDOCC) trial to estimate ICC values. Data on 5,140 patients from 84 primary care practices across Eastern Ontario, Canada were collected through chart abstraction. ICC estimates were calculated using an ANOVA approach and were calculated for all patients and separately for patient subgroups defined by condition (i.e., coronary artery disease, diabetes, chronic kidney disease, hypertension, dyslipidemia, and smoking). We compared ICC estimates between practices in which data were collected from a single physician versus those that had multiple participating physicians and between urban versus rural practices.
Results:
ICC estimates ranged from 0 to 0.173, with a median of 0.056. The median ICC estimate for dichotomous process outcomes (0.088) was higher than that for continuous clinical outcomes (0.035). ICC estimates calculated for single physician practices were higher than those for practices with multiple physicians for both process (average 3.9-times higher) and clinical measures (average 1.9-times higher). Urban practices tended to have higher process-of-care ICC estimates than rural practices, particularly for measuring lipid profiles and estimated glomerular filtration rates.
Conclusion:
To our knowledge, this is the most comprehensive summary of cardiovascular-related ICCs to be reported from Canadian primary care practices. Differences in ICC estimates based on practice structure and location highlight the importance of understanding the context in which external ICC estimates were determined prior to their use in sample size calculations. Failure to choose appropriate ICC estimates can have substantial implications for the design of a cluster randomized trial.
More Related Videos
06:16Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
06:55Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Related Concept Videos
Coronary Artery Disease IV: Preventive Measures
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...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
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...
Calculating and Interpreting the Linear Correlation Coefficient
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...