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Joint modeling of multivariate longitudinal measurements and survival data with applications to Parkinsons disease
In many clinical trials, studying neurodegenerative diseases including Parkinson’s disease (PD), multiple longitudinal outcomes are collected in order to fully explore the multidimensional impairment caused by these diseases. The follow-up of some patients can be stopped by some outcome-dependent terminal event, e.g. death and dropout. In this article, we develop a joint model that consists of a multilevel item response theory (MLIRT) model for the multiple longitudinal outcomes, and a Cox’s proportional hazard model with piecewise constant baseline hazards for the event time data. Shared random effects are use...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: He, B., Luo, S. Tags: Regular Articles Source Type: research

An adaptive clinical trials procedure for a sensitive subgroup examined in the multiple sclerosis context
The biomarker-adaptive threshold design (BATD) allows researchers to simultaneously study the efficacy of treatment in the overall group and to investigate the relationship between a hypothesized predictive biomarker and the treatment effect on the primary outcome. It was originally developed for survival outcomes for Phase III clinical trials where the biomarker of interest is measured on a continuous scale. In this paper, generalizations of the BATD to accommodate count biomarkers and outcomes are developed and then studied in the multiple sclerosis (MS) context where the number of relapses is a commonly used outcome. Th...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Riddell, C. A., Zhao, Y., Petkau, J. Tags: Regular Articles Source Type: research

Two-stage sampling designs for external validation of personal risk models
We propose a cost-effective sampling design and estimating procedure for validating personal risk models using right-censored cohort data. Validation involves using each subject’s covariates, as ascertained at cohort entry, in a risk model (specified independently of the data) to assign him/her a probability of an adverse outcome within a future time period. Subjects are then grouped according to the magnitudes of their assigned risks, and within each group, the mean assigned risk is compared with the probability of outcome occurrence as estimated using the follow-up data. Such validation presents two complications. ...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Whittemore, A. S., Halpern, J. Tags: Regular Articles Source Type: research

Simulating the contribution of a biospecimen and clinical data repository in a phase II clinical trial: A value of information analysis
In this study, we compared alternative data sets using a single model to assess value of information. Our findings suggest that the reductions in trial size range from 0% to 43%, depending on the amount of censoring in overall survival. The ability to expedite the accrual of patients for clinical trial studies using large data repositories that store data on inclusion/exclusion criteria and response to standard of care therapies demonstrated significant improvement in reducing the number of subjects needed to achieve similar end-results, as evaluated using value of information analysis with a limited number of parameters a...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Craig, B. M., Han, G., Munkin, M. K., Fenstermacher, D. Tags: Regular Articles Source Type: research

Step-up procedures for non-inferiority tests with multiple experimental treatments
Non-inferiority (NI) trials are becoming more popular. The NI of a new treatment compared with a standard treatment is established when the new treatment maintains a substantial fraction of the treatment effect of the standard treatment. A valid NI trial is also required to show assay sensitivity, the demonstration of the standard treatment having the expected effect with a size comparable to those reported in previous placebo-controlled studies. A three-arm NI trial is a clinical study that includes a new treatment, a standard treatment and a placebo. Most of the statistical methods developed for three-arm NI trials are d...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Kwong, K. S., Cheung, S. H., Hayter, A. J. Tags: Regular Articles Source Type: research

Notes on testing noninferiority in multivariate binary data under the matched-pair design
Since therapeutic efficacy is often measured by multiple endpoints, it will be of use if one can incorporate the information on various variables of response into procedures for testing noninferiority to improve power of a univariate test procedure for each individual variable. On the basis of the proposed mixed effects logistic regression model for multivariate binary data under the matched-pairs design, we develop procedures for testing noninferiority with respect to the odds ratio in multivariate binary data under the matched-pair design. We discuss use of Bonferroni’s and Scheffe’s methods to control the in...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Lui, K.-J., Chang, K.-C. Tags: Regular Articles Source Type: research

Adjusted inference procedures for the interobserver agreement in twin studies
We propose adjusted inference procedures for evaluating the agreement/disagreement of two raters in a clustered setting involving twins or paired body parts. These procedures include the construction of a confidence interval for the kappa statistic, a related test of statistical significance and a formula that facilitates sample size estimation. The results of a simulation study suggest that a simple adjustment using an estimated design effect will provide valid inferences. The methods proposed are illustrated using an example from the literature. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Dixon, S. N., Donner, A., Shoukri, M. M. Tags: Regular Articles Source Type: research

Comparing models for quantitative risk assessment: an application to the European Registry of foreign body injuries in children
Risk Assessment is the systematic study of decisions subject to uncertain consequences. An increasing interest has been focused on modeling techniques like Bayesian Networks since their capability of (1) combining in the probabilistic framework different type of evidence including both expert judgments and objective data; (2) overturning previous beliefs in the light of the new information being received and (3) making predictions even with incomplete data. In this work, we proposed a comparison among Bayesian Networks and other classical Quantitative Risk Assessment techniques such as Neural Networks, Classification Trees...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Berchialla, P., Scarinzi, C., Snidero, S., Gregori, D. Tags: Regular Articles Source Type: research

Preferential sampling and Bayesian geostatistics: Statistical modeling and examples
Preferential sampling refers to any situation in which the spatial process and the sampling locations are not stochastically independent. In this paper, we present two examples of geostatistical analysis in which the usual assumption of stochastic independence between the point process and the measurement process is violated. To account for preferential sampling, we specify a flexible and general Bayesian geostatistical model that includes a shared spatial random component. We apply the proposed model to two different case studies that allow us to highlight three different modeling and inferential aspects of geostatistical...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Cecconi, L., Grisotto, L., Catelan, D., Lagazio, C., Berrocal, V., Biggeri, A. Tags: Special Issue Articles Source Type: research

Multiscale measurement error models for aggregated small area health data
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser le...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Aregay, M., Lawson, A. B., Faes, C., Kirby, R. S., Carroll, R., Watjou, K. Tags: Special Issue Articles Source Type: research

A model to estimate the impact of changes in MMR vaccine uptake on inequalities in measles susceptibility in Scotland
An article published in 1998 by Andrew Wakefield in The Lancet (volume 351, pages 637–641) led to concerns surrounding the safety of the measles, mumps and rubella vaccine, by associating it with an increased risk of autism. The paper was later retracted after multiple epidemiological studies failed to find any association, but a substantial decrease in UK vaccination rates was observed in the years following publication. This paper proposes a novel spatio-temporal Bayesian hierarchical model with accompanying software (the R package CARBayesST) to simultaneously address three key epidemiological questions about vacc...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Napier, G., Lee, D., Robertson, C., Lawson, A., Pollock, K. G. Tags: Special Issue Articles Source Type: research

A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping
Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated det...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Baptista, H., Mendes, J. M., MacNab, Y. C., Xavier, M., Caldas-de-Almeida, J. Tags: Special Issue Articles Source Type: research

An intuitive Bayesian spatial model for disease mapping that accounts for scaling
In recent years, disease mapping studies have become a routine application within geographical epidemiology and are typically analysed within a Bayesian hierarchical model formulation. A variety of model formulations for the latent level have been proposed but all come with inherent issues. In the classical BYM (Besag, York and Mollié) model, the spatially structured component cannot be seen independently from the unstructured component. This makes prior definitions for the hyperparameters of the two random effects challenging. There are alternative model formulations that address this confounding; however, the issu...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Riebler, A., Sorbye, S. H., Simpson, D., Rue, H. Tags: Special Issue Articles Source Type: research

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs
This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-cov...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: MacNab, Y. C. Tags: Special Issue Articles Source Type: research

Spatial Bayesian surveillance for small area case event data
There has been little development of surveillance procedures for epidemiological data with fine spatial resolution such as case events at residential address locations. This is often due to difficulties of access when confidentiality of medical records is an issue. However, when such data are available, it is important to be able to affect an appropriate analysis strategy. We propose a model for point events in the context of prospective surveillance based on conditional logistic modeling. A weighted conditional autoregressive model is developed for irregular lattices to account for distance effects, and a Dirichlet tessel...
Source: Statistical Methods in Medical Research - August 25, 2016 Category: Statistics Authors: Rotejanaprasert, C., Lawson, A., Bolick-Aldrich, S., Hurley, D. Tags: Special Issue Articles Source Type: research