Presentation Title
Intracluster Correlation Coefficients in Healthcare Research
Abstract
In a cluster randomization trial, which are often used in healthcare research, randomization occurs at the group level not at the individual level. It is often more practical to randomize an entire practice to a treatment rather than each individual patient. Clustering is very common in behavioral health research because interventions are often meant to be taken on by an entire practice. However, when randomization occurs at the practice level and outcomes are measured on the patient level, it can lead to some problems in the statistical analysis. Most standard statistical methods assume independence between individuals, which is true for a typical randomized experiment. However, there are many factors that cause individuals who visit the same practice to not be independent. This lack of independence must be accounted for in the analysis using intracluster correlation coefficients (ICC). ICCs are important to use for calculating the sample size in a study and can impact the statistical power of the clinical trial if not used correctly. This presentation will show what ICCs are, how to calculate them, and how they were used in the IBHPC study at UVM.
Primary Faculty Mentor Name
Abigail Crocker
Faculty/Staff Collaborators
Abigail Crocker
Status
Undergraduate
Student College
College of Engineering and Mathematical Sciences
Second Student College
Graduate College
Program/Major
Statistics
Second Program/Major
Biostatistics
Primary Research Category
Health Sciences
Intracluster Correlation Coefficients in Healthcare Research
In a cluster randomization trial, which are often used in healthcare research, randomization occurs at the group level not at the individual level. It is often more practical to randomize an entire practice to a treatment rather than each individual patient. Clustering is very common in behavioral health research because interventions are often meant to be taken on by an entire practice. However, when randomization occurs at the practice level and outcomes are measured on the patient level, it can lead to some problems in the statistical analysis. Most standard statistical methods assume independence between individuals, which is true for a typical randomized experiment. However, there are many factors that cause individuals who visit the same practice to not be independent. This lack of independence must be accounted for in the analysis using intracluster correlation coefficients (ICC). ICCs are important to use for calculating the sample size in a study and can impact the statistical power of the clinical trial if not used correctly. This presentation will show what ICCs are, how to calculate them, and how they were used in the IBHPC study at UVM.