eprintid: 1490782
rev_number: 23
eprint_status: archive
userid: 608
dir: disk0/01/49/07/82
datestamp: 2016-05-07 22:49:04
lastmod: 2021-10-04 00:52:36
status_changed: 2016-09-14 13:30:48
type: article
metadata_visibility: show
creators_name: Yelland, LN
creators_name: Sullivan, TR
creators_name: Pavlou, M
creators_name: Seaman, SR
title: Analysis of Randomised Trials Including Multiple Births When Birth Size Is Informative
ispublished: pub
divisions: UCL
divisions: B04
divisions: C06
divisions: F61
keywords: clustering, generalised estimating equations, informative cluster size, multiple births, statistical methodology
note: This is the peer reviewed version of the following article: Yelland, LN; Sullivan, TR; Pavlou, M; Seaman, SR; (2015) Analysis of Randomised Trials Including Multiple Births When Birth Size Is Informative. Paediatric and Perinatal Epidemiology, 29 (6) pp. 567-575, which has been published in final form at: http://dx.doi.org/10.1111/ppe.12228. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving (http://olabout.wiley.com/WileyCDA/Section/id-828039.html#terms).
abstract: BACKGROUND: Informative birth size occurs when the average outcome depends on the number of infants per birth. Although analysis methods have been proposed for handling informative birth size, their performance is not well understood. Our aim was to evaluate the performance of these methods and to provide recommendations for their application in randomised trials including infants from single and multiple births. METHODS: Three generalised estimating equation (GEE) approaches were considered for estimating the effect of treatment on a continuous or binary outcome: cluster weighted GEEs, which produce treatment effects with a mother-level interpretation when birth size is informative; standard GEEs with an independence working correlation structure, which produce treatment effects with an infant-level interpretation when birth size is informative; and standard GEEs with an exchangeable working correlation structure, which do not account for informative birth size. The methods were compared through simulation and analysis of an example dataset. RESULTS: Treatment effect estimates were affected by informative birth size in the simulation study when the effect of treatment in singletons differed from that in multiples (i.e. in the presence of a treatment group by multiple birth interaction). The strength of evidence supporting the effectiveness of treatment varied between methods in the example dataset. CONCLUSIONS: Informative birth size is always a possibility in randomised trials including infants from both single and multiple births, and analysis methods should be pre-specified with this in mind. We recommend estimating treatment effects using standard GEEs with an independence working correlation structure to give an infant-level interpretation.
date: 2015-11
date_type: published
official_url: http://dx.doi.org/10.1111/ppe.12228
oa_status: green
full_text_type: other
pmcid: PMC4847643
language: eng
primo: open
primo_central: open_green
article_type_text: Journal Article
verified: verified_manual
elements_id: 1051029
doi: 10.1111/ppe.12228
lyricists_name: Pavlou, Menelaos
lyricists_id: MPAVL11
full_text_status: public
publication: Paediatric and Perinatal Epidemiology
volume: 29
number: 6
pagerange: 567-575
event_location: England
issn: 1365-3016
citation:        Yelland, LN;    Sullivan, TR;    Pavlou, M;    Seaman, SR;      (2015)    Analysis of Randomised Trials Including Multiple Births When Birth Size Is Informative.                   Paediatric and Perinatal Epidemiology , 29  (6)   pp. 567-575.    10.1111/ppe.12228 <https://doi.org/10.1111/ppe.12228>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1490782/1/Pavlou_Informative%20Cluster%20Size%20for%20Perinatal%20Trials%20Main%20Article%20Accepted.pdf