Jian Qing Shi

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There is no simple method of correcting for publication bias in systematic reviews. We suggest a sensitivity analysis in which different patterns of selection bias can be tested against the fit to the funnel plot. Publication bias leads to lower values, and greater uncertainty, in treatment effect estimates. Two examples are discussed. An appendix lists the(More)
As a result of their good performance in practice and their desirable analytical properties, Gaussian process regression models are becoming increasingly of interest in statistics, engineering and other fields. However, two major problems arise when the model is applied to a large data-set with repeated measurements. One stems from the systematic(More)
Two-level data with hierarchical structure and mixed continuous and polytomous data are very common in biomedical research. In this article, we propose a maximum likelihood approach for analyzing a latent variable model with these data. The maximum likelihood estimates are obtained by a Monte Carlo EM algorithm that involves the Gibbs sampler for(More)
Publication bias is a major problem, perhaps the major problem, in meta-analysis (or systematic reviews). Small studies are more likely to be published if their results are 'significant' than if their results are negative or inconclusive, and so the studies available for review are biased in favour of those with positive outcomes. Correcting for this bias(More)
Grouped dose measures, heterogeneity and publication bias are three major problems for meta-analysis in trend estimation. In this paper, we propose a model that allows for arbitrarily aggregated dose levels, and show that the resulting estimates and standard errors can be quite different from those given by the usual assigned value method. Based on fitting(More)
A Gaussian process functional regression model is proposed for the analysis of batch data. Covariance structure and mean structure are considered simultaneously, with the covariance structure modeled by a Gaussian process regression model and the mean structure modeled by a functional regression model. The model allows the inclusion of covariates in both(More)
This paper presents analysis of the standing–up manoeuvre in paraplegia considering the body supportive forces as a potential feedback source in FES-assisted standing–up. The analysis investigates the significance of particular feedback signals to the human body centreof-mass (COM) trajectory reconstruction. Two nonlinear empirical modeling methods are(More)