BMJ  2005;330:142-144 (15 January), doi:10.1136/bmj.330.7483.142

Education and debate

Clustering by health professional in individually randomised trials

¹ MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 2SR

Patient outcomes in many randomised trials depend crucially on the health professional delivering the intervention, but the resulting clustering is rarely considered in the analysis

The first 150 words of the full text of this article appear below.

Introduction

Almost all trials that randomise individuals assume that the observed outcomes of participants are independent. The validity of this assumption is doubtful, however, in some situations. One example is when more than one health professional (such as surgeons, nurses, general practitioners, or therapists) delivers a non-pharmaceutical intervention to participants. Because health professionals may vary in their effectiveness, observations on participants treated by the same professional may be somewhat similar or clustered. Clustering of outcomes may also appear less obviously (such as in clustering by centre in a multicentre trial) or in a more dominant form (as in cluster randomised trials). In each of these situations the assumption of independence is violated, which means that standard statistical methods are invalid and may give misleading conclusions. The presence of clustering in a trial inflates standard errors and reduces the effective sample size, thus reducing the power of the trial. We examine the . . . [Full text of this article]

Types of clustering

Is clustering common?

Is clustering important?

Discussion

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