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Multiple imputation by chained equations is a flexible and practical approach to handling missing data. We describe the principles of the method and show how to impute categorical and quantitative variables, including skewed variables. We give guidance on how to specify the imputation model and how many imputations are needed. We describe the practical(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)
CONTEXT Circulating concentration of lipoprotein(a) (Lp[a]), a large glycoprotein attached to a low-density lipoprotein-like particle, may be associated with risk of coronary heart disease (CHD) and stroke. OBJECTIVE To assess the relationship of Lp(a) concentration with risk of major vascular and nonvascular outcomes. STUDY SELECTION Long-term(More)
Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I(2) statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate(More)
CONTEXT Plasma fibrinogen levels may be associated with the risk of coronary heart disease (CHD) and stroke. OBJECTIVE To assess the relationships of fibrinogen levels with risk of major vascular and with risk of nonvascular outcomes based on individual participant data. DATA SOURCES Relevant studies were identified by computer-assisted searches, hand(More)
The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and(More)
Conducting a sound skin sensitization risk assessment prior to the introduction of new ingredients and products into the market place is essential. The process by which low-molecular-weight chemicals induce and elicit skin sensitization is dependent on many factors, including the ability of the chemical to penetrate the skin, react with protein, and trigger(More)
Adjustment for baseline variables in a randomized trial can increase power to detect a treatment effect. However, when baseline data are partly missing, analysis of complete cases is inefficient. We consider various possible improvements in the case of normally distributed baseline and outcome variables. Joint modelling of baseline and outcome is the most(More)
Multivariate meta-analysis is increasingly used in medical statistics. In the univariate setting, the non-iterative method proposed by DerSimonian and Laird is a simple and now standard way of performing random effects meta-analyses. We propose a natural and easily implemented multivariate extension of this procedure which is accessible to applied(More)
OBJECTIVE To estimate the relation between alcohol consumption and risk of death, the level of alcohol consumption at which risk is least, and how these vary with age and sex. DESIGN Analysis using published systematic reviews and population data. SETTING England and Wales in 1997. MAIN OUTCOME MEASURES Death from any of the following causes: cancer(More)