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Thread: When do sample size calculations need to adjust for clustering?

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    When do sample size calculations need to adjust for clustering?




    I am aware that sample size calculations for cluster RCTs must adjust for clustered data. I would like to understand better if such adjustment might be necessary for other study designs. For instance, I am working on a nested case-control study to identify clinical and socio-demographic factors associated with patient retention. We will use medical record data collected from health facilities. All patients from all sites meeting the inclusion criteria will be included in the study (no sampling per se). The study is not trying to make any inference about any population parameter.

    Should the sample size calculation adjust for clustering? After all, it is likely that the data abstracted from medical records will be clustered. At the same time, should the analysis adjust for clustering?

    How about if the study were a cluster RCT and all patients from all sites meeting the inclusion criteria will be included in the study--would the sample size calculation need to adjust for clustering?

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    Re: When do sample size calculations need to adjust for clustering?


    I did not understand your message completely but I can say this: whenever the data are split into units and the variance of the studied characteristic may be different in different units, most calculations must be adjusted for this type of partitioning, including power calculations.

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