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When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment-covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. © 2014 The Authors. Research Synthesis Methods published by John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The authors examined the extent of the relationship between a Consultation satisfaction questionnaire and Patient enablement instrument scores and professionally assessed consultation competence scores of senior medical students. Three analyses were performed: (i) linear regression with mean overall competence score as response variable; (ii) sensitivity and specificity calculations using patient scores to classify competence; (iii) a repeated measures model with consultation-specific competence score as response variable. One hundred and nineteen students and 388 patients took part. Consultation satisfaction and enablement scores were weakly correlated with overall and consultation specific competence scores (correlation coefficient 0.16 to 0.44). 'Satisfaction with professional care' had a sensitivity of 0.68, specificity of 0.72 and positive and negative predictive values of 0.32 and 0.92 respectively. It is concluded that patient and professional assessments may complement, but do not replace, each other. Levels of patient satisfaction should not be used as proxy measures of the quality of consultation competence. [ABSTRACT FROM AUTHOR]