2004
DOI: 10.1111/j.1471-0528.2004.00059.x
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How should randomised trials including multiple pregnancies be analysed?

Abstract: Objective To compare the effects of four methods of analysis on the results of randomised controlled trials that recruit women with multiple pregnancies and measure outcomes on their babies. Design Analysis of one real and two simulated data sets.Setting Secondary analysis of perinatal randomised controlled trials.Population Randomised controlled trials including women with multiple pregnancies.Methods The analytical methods compared were (a) assuming independence among babies, (b) analysing outcomes per women… Show more

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Cited by 107 publications
(94 citation statements)
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References 14 publications
(10 reference statements)
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“…In the analysis of neonatal outcomes, neonates from multiple births were treated as independent, but the eff ect of adjusting for potential clustering was also assessed. 14 The focus of the primary analysis was the main eff ects of the fi ve intervention pairs analysed separately. Pairwise interactions were planned if the analyses showed any statistically signifi cant main eff ects for the primary outcome only.…”
Section: Discussionmentioning
confidence: 99%
“…In the analysis of neonatal outcomes, neonates from multiple births were treated as independent, but the eff ect of adjusting for potential clustering was also assessed. 14 The focus of the primary analysis was the main eff ects of the fi ve intervention pairs analysed separately. Pairwise interactions were planned if the analyses showed any statistically signifi cant main eff ects for the primary outcome only.…”
Section: Discussionmentioning
confidence: 99%
“…Multiple births are an important subgroup to consider in such trials, since multiples account for around a quarter of all preterm births and half of all twins are born preterm 1. Including multiple births in a trial can be challenging due to the correlation between outcomes of infants from the same birth that results from shared environmental and genetic factors 2 3. Correlated or clustered data are common in health research and methods for analysing these types of data are widely discussed 4–8.…”
Section: Introductionmentioning
confidence: 99%
“…We also conducted a sensitivity analysis including multiple births, with clustering of outcomes accounted for using an approach previously published. 87 This adapts methodology previously created for use with cluster RCTs, assuming that each woman is regarded as the 'cluster' and her number of offspring as the cluster size. A chi-squared test was used to compare the total number of women or their infants who had at least one AE or serious adverse event (SAE).…”
Section: Fetal and Maternal Birth Outcomesmentioning
confidence: 99%