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In this appendix we provide motivation and considerations for assessing the risk of bias for each of the items included in the Cochrane Collaboration's risk of bias assessment tool. More detail is provided in the Cochrane Handbook for Systematic Reviews of Interventions. w1 Selection bias The unique strength of randomization is that, if successfully(More)
Asymmetry in funnel plots may indicate publication bias in meta-analysis, but the shape of the plot in the absence of bias depends on the choice of axes. We evaluated standard error, precision (inverse of standard error), variance, inverse of variance, sample size and log sample size (vertical axis) and log odds ratio, log risk ratio and risk difference(More)
Publication and selection biases in meta-analysis are more likely to affect small studies, which also tend to be of lower methodological quality. This may lead to "small-study effects," where the smaller studies in a meta-analysis show larger treatment effects. Small-study effects may also arise because of between-trial heterogeneity. Statistical tests for(More)
OBJECTIVE To examine whether the association of inadequate or unclear allocation concealment and lack of blinding with biased estimates of intervention effects varies with the nature of the intervention or outcome. DESIGN Combined analysis of data from three meta-epidemiological studies based on collections of meta-analyses. DATA SOURCES 146(More)
Publication bias and related bias in meta-analysis is often examined by visually checking for asymmetry in funnel plots of treatment effect against its standard error. Formal statistical tests of funnel plot asymmetry have been proposed, but when applied to binary outcome data these can give false-positive rates that are higher than the nominal level in(More)
BACKGROUND Impaired fetal growth may be a risk factor for asthma although evidence in children is conflicting and there are few data in adults. Little is known about risk factors which may influence asthma in late childhood or early adult life. Whilst there are clues that fatness may be important, this has been little studied in young adults. The relations(More)
Biases in systematic reviews and meta-analyses may be examined in 'meta-epidemiological' studies, in which the influence of trial characteristics such as measures of study quality on treatment effect estimates is explored. Published studies to date have analysed data from collections of meta-analyses with binary outcomes, using logistic regression models(More)