Additional file 3 of A general framework for comparative Bayesian meta-analysis of diagnostic studies

Simulation Study of the Modeling Approach. (PDF 491 KB

Additional file 1 of A general framework for comparative Bayesian meta-analysis of diagnostic studies

Simulation Study for the Selection of Appropriate Statistics for a Comparative DTA Review. (PDF 1208 KB

Additional file 4 of A general framework for comparative Bayesian meta-analysis of diagnostic studies

Visceral Leishmaniasis Data. (PDF 44 KB

Exploring the Clustering Effect of the Frailty Survival Model by Means of the Brier Score

<p>In this article, the Brier score is used to investigate the importance of clustering for the frailty survival model. For this purpose, two versions of the Brier score are constructed, i.e., a “conditional Brier score” and a “marginal Brier score.” Both versions of the Brier score show how the clustering effects and the covariate effects affect the predictive ability of the frailty model separately. Using a Bayesian and a likelihood approach, point estimates and 95% credible/confidence intervals are computed. The estimation properties of both procedures are evaluated in an extensive simulation study for both versions of the Brier score. Further, a validation strategy is developed to calculate an internally validated point estimate and credible/confidence interval. The ensemble of the developments is applied to a dental dataset.</p

Additional file 1 of DMC reports in the 21st century: towards better tools for decision-making

Additional file 1. Source outputs from the Xanomeline Clinical Study Report (Word doc). Program code in R: https://github.com/DMC21cent/DMC21cent

Identifying influential observations in a Bayesian multi-level mediation model

Increasingly complex models are being fit to data these days. This is especially the case for Bayesian modelling making use of Markov chain Monte Carlo methods. Tailored model diagnostics are usually lacking behind. This is also the case for Bayesian mediation models. In this paper, we developed a method for the detection of influential observations for a popular mediation model and its extensions in a Bayesian context. Detection of influential observations is based on the case-deletion principle. Importance sampling with weights which take advantage of the dependence structure in hierarchical models is utilized in order to identify the part of the model which is influenced most. We make use of the variance of log importance sampling weights as the measure of influence. It is demonstrated that this approach is useful when interest lies in the impact of individual observations on a subset of model parameters. The method is illustrated on a three-level data set from the field of nursing research, which was previously used to fit a mediation model of patient satisfaction with care. We focused on influential cases on both the second and the third level of the data.</p

Posterior mean odds ratios and 95% credible intervals of the regression coefficients for the binary longitudinal models with response: CD4 counts ≥500 cells/μL.

Posterior mean odds ratios and 95% credible intervals of the regression coefficients for the binary longitudinal models with response: CD4 counts ≥500 cells/μL.</p

Predicted posterior median CD4 counts trajectory by covariate strata for the slope of CD4 count model, with 95% prediction intervals.

A. baseline CD4 count (cells/μL), B. sex, C. baseline age (years), D. baseline log10 VL (copies/mL). Median predicted CD4 counts from model 1, is plotted. The red, black or blue dots represent predicted median CD4 count at different time points, and the bars are the whiskers.</p

The effect of changing from a Gaussian to a skew-normal on the estimated regression coefficients, with 95% credible intervals, in the slope model.

The effect of changing from a Gaussian to a skew-normal on the estimated regression coefficients, with 95% credible intervals, in the slope model.</p

The results of Scenario B2.

<p>Percentage of data sets in which the true number of clusters was found, with the mode of the estimated number of classes in parentheses.</p