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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)
In 2003, the QUADAS tool for systematic reviews of diagnostic accuracy studies was developed. Experience, anecdotal reports, and feedback suggested areas for improvement; therefore, QUADAS-2 was developed. This tool comprises 4 domains: patient selection, index test, reference standard, and flow and timing. Each domain is assessed in terms of risk of bias,(More)
1Department of Social Medicine, University of Bristol, Bristol BS8 2PR 2MRC Biostatistics Unit, Institute of Public Health, Cambridge CB2 0SR 3Clinical Epidemiology and Biostatistics Unit, Murdoch Children’s Research Institute, and University of Melbourne, Parkville, Victoria 3052, Australia 4Cancer and Statistical Methodology Groups, MRC Clinical Trials(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)
BACKGROUND Insufficient data are available from single cohort studies to allow estimation of the prognosis of HIV-1 infected, treatment-naive patients who start highly active antiretroviral therapy (HAART). The ART Cohort Collaboration, which includes 13 cohort studies from Europe and North America, was established to fill this knowledge gap. METHODS We(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 Highly active antiretroviral therapy (HAART) is being scaled up in developing countries. We compared baseline characteristics and outcomes during the first year of HAART between HIV-1-infected patients in low-income and high-income settings. METHODS 18 HAART programmes in Africa, Asia, and South America (low-income settings) and 12 HIV cohort(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)
Published evidence suggests that aspects of trial design lead to biased intervention effect estimates, but findings from different studies are inconsistent. This study combined data from 7 meta-epidemiologic studies and removed overlaps to derive a final data set of 234 unique meta-analyses containing 1973 trials. Outcome measures were classified as(More)