Decision models are usually populated 1 parameter at a time, with 1 item of information informing each parameter. Often, however, data may not be available on the parameters themselves but on several functions of parameters, and there may be more items of information than there are parameters to be estimated. The authors show how in these circumstances all the model parameters can be estimated ...

Finding genetic biomarkers and a search of geneticepidemiological factors, can be formulated as a statistical problem of variable selection, where from a large set of candidates a small number of trait-associated predictors are identified. We illustrate this by analyzing the data available for Chronic Fatigue Syndrome (CFS). CFS is a complex disease from several aspects, e.g. difficult to diagn...

Purpose Measurement error is an important source of bias in epidemiological studies. We illustrate three approaches to sensitivity analysis for the effect of measurement error: imputation of the 'true' exposure based on specifying the sensitivity and specificity of the measured exposure (SS); direct imputation (DI) using a regression model for the predictive values; and adjustment based on a fu...

It is widely recognized that the mixed linear model is an important tool for parameter estimation in the analysis of complex pedigrees, which includes both pedigree and genomic information, and where mutually dependent genetic factors are often assumed to follow multivariate normal distributions of high dimension. We have developed a Bayesian statistical method based on the decomposition of the...

Many clinical trials and other medical and reliability studies generate both longitudinal (repeated measurement) and survival (time to event) data. Many well-established methods exist for analyzing such data separately, but these may be inappropriate when the longitudinal variable is correlated with patient health status, hence the survival endpoint (as well as the possibility of study dropout)...

Markov transition models are frequently used to model disease progression. The authors show how the solution to Kolmogorov's forward equations can be exploited to map between transition rates and probabilities from probability data in multistate models. They provide a uniform, Bayesian treatment of estimation and propagation of uncertainty of transition rates and probabilities when 1) observati...

It is often unclear what specific adaptive trial design features lead to an efficient design which is also feasible to implement. This article describes the preparatory simulation study for a Bayesian response-adaptive dose-finding trial design. Dexamethasone for Excessive Menstruation aims to assess the efficacy of Dexamethasone in reducing excessive menstrual bleeding and to determine the bes...

Economic evaluation of health care interventions based on decision analytic modelling can generate valuable information for health policy decision makers. However, the usefulness of the results obtained depends on the quality of the data input into the model; that is, the accuracy of the estimates for the costs, effectiveness, and transition probabilities between the different health states of ...

Many previous studies have suggested a link between alcohol outlets and assaultive violence. In this paper, we evaluate the impact of the "1992 Civil Unrest" in Los Angeles (which followed the "Rodney King incident"), in which many alcohol outlets were damaged leading to a decrease in alcohol outlet density, on crime. We leverage the natural experiment created by the closure of alcohol outlets ...

BACKGROUND The early identification of influenza outbreaks has became a priority in public health practice. A large variety of statistical algorithms for the automated monitoring of influenza surveillance have been proposed, but most of them require not only a lot of computational effort but also operation of sometimes not-so-friendly software. RESULTS In this paper, we introduce FluDetWeb, a...