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SUMMARY:"The Implications of Differential Clustering for the Analysis of B
 inary Outcome Measures" - Dr Chris Roberts\, University of Manchester
DTSTART:20160223T143000Z
DTEND:20160223T153000Z
UID:TALK63428@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Abstract: In trials of non-pharmacological treatments clusteri
 ng of patients may occur due to randomisation or due to the nesting of pat
 ients in therapist or therapy groups. This talk will consider the implicat
 ion of heterogeneity of the clustering effect where the outcome measure is
  binary.\n\nHeterogeneity of the clustering effect may arise in trials of 
 group administered or therapist treatment where a clustered therapy is com
 pared with a placebo or pharmacological control. This leads to what has be
 en called a partially nested design where there is clustering in one arm b
 ut not the comparator.\n\nHeteroscedasticity of the clustering effect can 
 arise in cluster randomised trials. Statistical analysis of cluster random
 ised trials generally assumes that the intra-cluster correlation coefficie
 nt (ICC) is the same in all arms. This assumption can be justified by rand
 omisation provided the clustering effect is due to the baseline characteri
 stics. If\, instead\, the magnitude of the clustering effect is caused by 
 the intervention\, the ICC may differ between trial arms.\n\nAfter reviewi
 ng the situation where the outcome measure is continuous\, the robustness 
 of methods of analysis for binary outcomes will be considered.
LOCATION:Large  Seminar Room\, 1st Floor\, Institute of Public Health\, Un
 iversity Forvie Site\, Robinson Way\, Cambridge
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