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The use of a cluster design can lead to selection bias at either the level of cluster or the individual.
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Some of the biases associated with the use of cluster designs can be avoided with careful attention to the design.
The cluster intervention design can help to reduce both effects.
The two effect estimates generated (one from the stepped-wedge design, one from the parallel cluster trial design) can be compared in a ratio of ratios.
Cluster randomised designs can increase risk of selection bias.
Clustered sampling: this sampling design can be applied when homogeneous groups (clusters) composed by distinct units can be identified in a population.
Based on groups of interest's similarities (groups' members overlapping), the feasibility of performing the following sampling designs will be analyzed, in this order: 1. Clustered sampling: this sampling design can be applied when homogeneous groups (clusters) composed by distinct units can be identified in a population.
The original cohort sample was randomly selected by using a two stage cluster design, full details of which can be found on-line [ 30].
This confounding of level-1 (individual) and level-2 (cluster) design issues in a single weight can result in biased estimates.
The main consequence of a cluster design is that the outcomes for subjects within the same cluster can not be assumed to be independent.
The study design can also be described as a non-randomised cluster-allocated trial.
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