What is coefficient of variation for cluster sizes?

2019-10-27

What is coefficient of variation for cluster sizes?

CV is the coefficient of variation of cluster size. This design effect can be used with an appropriately weighted cluster-level analysis for binary or continuous outcomes. 50,54,55As individual-level analyses are more efficient, it provides an overestimate of sample size required for most individual level analyses.

How do you analyze cluster randomized trials?

The traditional approach to the analysis of cluster randomized trials has been to calculate a summary measure for each cluster, such as a cluster mean or proportion. Because each cluster then provides only one data point, the data can be considered to be independent, allowing standard statistical tests to be used.

What is ICC in cluster randomized trial?

Intraclass correlation coefficient (ICC) is used to determine the degree of within-cluster dependence and it plays an important role in estimating sample size for cluster randomized trials [3].

How many clusters are in a cluster randomized trial?

The minimum number of clusters required to maintain the type I error rate at 5% has been suggested to be around 30–40 clusters for mixed models and 40–50 for GEEs,1,9 although depending on specific trial characteristics, a larger number of clusters may be required.

How do you calculate sample size for a cluster randomized trial?

The SE is minimal for the following cluster size [9], [10]:(2) n = ( 1 − ρ ) c ρ s and the number of clusters then can be calculated as K = B / (c + sn). So the optimal sample size per cluster decreases as the ICC goes up and increases as the cluster-to-person cost ratio c/s goes up.

What is a cluster randomized design?

Cluster randomised trials (CRTs) involve randomisation of groups (clusters) of individuals to control or intervention conditions.1 The CRT design is commonly used to evaluate non-drug interventions, such as policy and service delivery interventions.

What is an example of cluster analysis?

Many businesses use cluster analysis to identify consumers who are similar to each other so they can tailor their emails sent to consumers in such a way that maximizes their revenue. For example, a business may collect the following information about consumers: Percentage of emails opened. Number of clicks per email.

What is a cluster-randomized design?

How is ICC calculated?

The ICC serves as a quantitative estimate of this aspect of reliability. Very generally speaking, the ICC is calculated as a ratio ICC = (variance of interest) / (total variance) = (variance of interest) / (variance of interest + unwanted variance).

How do you know how many clusters a sample is?

Members of a sample are selected individually. Determine groups: Determine the number of groups by including the same average members in each group. Make sure each of these groups are distinct from one another. Select clusters: Choose clusters by applying a random selection.

How do you calculate sample size in cluster sampling?

This is calculated as the between-cluster standard deviation divided by the parameter of interest, i.e. the proportion, rate or mean, within each cluster. This measure is particularly useful when the primary outcome variable is a rate, as an ICC cannot be calculated.

What is the coefficient of variation of cluster size in clinical trials?

For trials randomizing UK general practices the coefficient of variation of cluster size depends on variation in practice list size, variation in incidence or prevalence of the medical condition under examination, and practice and patient recruitment strategies, and for many trials is expected to be ∼0.65.

How to calculate the sample size of a cluster randomized trial?

Background:The use of cluster randomized trials (CRTs) is increasing, along with the variety in their design and analysis. The simplest approach for their sample size calculation is to calculate the sample size assuming individual randomization and inflate this by a design effect to account for randomization by cluster.

What are the disadvantages of cluster randomization in clinical trials?

A simple approach to sample size calculation A consequence of clustering is that the information gained is less than that in an individually randomized trial of the same size, making randomization by cluster less efficient.

Which coefficient of variation should be used in sample size calculations?

The more appropriate cv to use in a sample size calculation, that for all analysed practices ( Figure 2, bottom line), is at a maximum of 0.71 at a mean cluster size of five and tends towards the underlying coefficient of variation of practice list sizes, 0.63, as mean cluster size increases.