All of the included MAO-B inhibitors were effective compared to placebo when given as monotherapy. Combination therapy with MAO-B inhibitors and levodopa showed that all three MAO-B inhibitors were effective compared to placebo, but selegiline was the most effective drug.

In a recent paper we extended and refined some tools introduced by O'Hagan for criticism of Bayesian hierarchical models. Especially, avoiding double use of data by a data-splitting approach was a main concern. Such tools can be applied at each node of the model, with a view to diagnosing problems of model fit at any point in the model structure. As O'Hagan, we investigated a Gaussian model of one-way analysis of variance. Through extensive Markov chain Monte Carlo simulations it was shown that our method detects model misspecification about as well as the one of O'Hagan, when this is properly calibrated, while retaining the desired false warning probability for data generated from the assumed model. In the present paper, we suggest some new measures of conflict based on tail probabilities of the so-called integrated posterior distributions introduced in our recent paper. These new measures are equivalent to the measure applied in the latter paper in simple Gaussian models, but seem more appropriately adjusted to deviations from normality and to conflicts not concerning location parameters. A general linear normal model with known covariance matrices is considered in detail. Copyright (c) 2009 Board of the Foundation of the Scandinavian Journal of Statistics.

O'Hagan ("Highly Structured Stochastic Systems", Oxford University Press, Oxford, 2003) introduces some tools for criticism of Bayesian hierarchical models that can be applied at each node of the model, with a view to diagnosing problems of model fit at any point in the model structure. His method relies on computing the posterior median of a conflict index, typically through Markov chain Monte Carlo simulations. We investigate a Gaussian model of one-way analysis of variance, and show that O'Hagan's approach gives unreliable false warning probabilities. We extend and refine the method, especially avoiding double use of data by a data-splitting approach, accompanied by theoretical justifications from a non-trivial special case. Through extensive numerical experiments we show that our method detects model mis-specification about as well as the method of O'Hagan, while retaining the desired false warning probability for data generated from the assumed model. This also holds for Student's-"t" and uniform distribution versions of the model. Copyright 2007 Board of the Foundation of the Scandinavian Journal of Statistics..

In this paper, we present a general formulation of an algorithm, the adaptive independent chain (AIC), that was introduced in a special context in Ga˚semyr et al. [Methodol. Comput. Appl. Probab. 3 (2001)]. The algorithm aims at producing samples from a specific target distribution P, and is an adaptive, non-Markovian version of the Metropolis-Hastings independent chain. A certain parametric class of possible proposal distributions is fixed, and the parameters of the proposal distribution are updated periodically on the basis of the recent history of the chain, thereby obtaining proposals that get ever closer to P. We show that under certain conditions, the algorithm produces an exact sample from P in a finite number of iterations, and hence that it converges to P. We also present another adaptive algorithm, the componentwise adaptive independent chain (CAIC), which may be an alternative in particular in high dimensions. The CAIC may be regarded as an adaptive approximation to the Gibbs sampler updating parametric approximations to the conditionals of P.

Purpose To investigate the comparative effectiveness of dopamine agonists and monoamine oxidase type-B (MAO-B) inhibitors available for treatment of Parkinson's disease. Methods We performed a systematic literature search identifying randomized controlled trials investigating 4 dopamine agonists (cabergoline, pramipexole, ropinirole, rotigotine) and 3 MAO-B inhibitors (selegiline, rasagiline, safinamide) for Parkinson's disease. We extracted and pooled data from included clinical trials in a joint model allowing both direct and indirect comparison of the seven drugs. We considered dopamine agonists and MAO-B inhibitors given as monotherapy or in combination with levodopa. Selected endpoints were change in the Unified Parkinson's Disease Rating Scale (UPDRS) score, serious adverse events and withdrawals. We estimated the relative effectiveness of each dopamine agonist and MAO-B inhibitor versus comparator drug. Results Altogether, 79 publications were included in the analysis. We found all the investigated drugs to be effective compared with placebo when given as monotherapy except safinamide. When considering combination treatment, the estimated relative