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This paper extends the concept to a multi\u2010level setting, displaying one level at a time, adjusted for the other levels, as well as for covariates at all levels. These level\u2010adjusted funnel plots are based on a Markov chain Monte Carlo fit of a random effects model, translating the estimated model parameters to predicted marginal expectations. Working within the estimation framework, we accommodate outlying institutions using heavy\u2010tailed random effects distributions. We also develop computer\u2010efficient methods to compute predicted probabilities in the case of dichotomous outcome data and various random effect distributions. We apply the method to a data set on prophylactic antibiotics in gallstone surgery. 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