# Journal of the Royal Statistical Society: Series C (Applied Statistics)

**Summary.**Medical imaging data are often valuable in evaluating disease and therapeutic effects. However, in formal assessment of treatment efficacy, it is usual to discard most of the rich information within the image, instead relying on simple summary measures. This reflects the absence of satisfactory statistical tools for the description and analysis of variability between images. We present extended...

**Summary.**Treatment of complex diseases such as cancer, leukaemia, acquired immune deficiency syndrome and depression usually follows complex treatment regimes consisting of time varying multiple courses of the same or different treatments. The goal is to achieve the largest overall benefit defined by a common end point such as survival. Adaptive treatment strategy refers to a sequence of treatments...

**Summary.**The cure fraction (the proportion of patients who are cured of disease) is of interest to both patients and clinicians and is a useful measure to monitor trends in survival of curable disease. The paper extends the non‐mixture and mixture cure fraction models to estimate the proportion cured of disease in population‐based cancer studies by incorporating a finite mixture of two Weibull distributions...

**Summary.**We consider joint spatial modelling of areal multivariate categorical data assuming a multiway contingency table for the variables, modelled by using a log‐linear model, and connected across units by using spatial random effects. With no distinction regarding whether variables are response or explanatory, we do not limit inference to conditional probabilities, as in customary spatial logistic...

**Summary.**Advances in understanding the biological underpinnings of many cancers have led increasingly to the use of molecularly targeted anticancer therapies. Because the platelet‐derived growth factor receptor (PDGFR) has been implicated in the progression of prostate cancer bone metastases, it is of great interest to examine possible relationships between PDGFR inhibition and therapeutic outcomes...

**Summary.**A multivariate non‐linear time series model for road safety data is presented. The model is applied in a case‐study into the development of a yearly time series of numbers of fatal accidents (inside and outside urban areas) and numbers of kilometres driven by motor vehicles in the Netherlands between 1961 and 2000. The model accounts for missing entries in the disaggregated numbers of kilometres...

**Summary.**As biological knowledge accumulates rapidly, gene networks encoding genomewide gene–gene interactions have been constructed. As an improvement over the standard mixture model that tests all the genes identically and independently distributed

*a priori*, Wei and co‐workers have proposed modelling a gene network as a discrete or Gaussian Markov random field (MRF) in a mixture model to analyse...

**Summary.**Motivated by the problem of predicting chemical deposition in eastern USA at weekly, seasonal and annual scales, the paper develops a framework for joint modelling of point‐ and grid‐referenced spatiotemporal data in this context. The hierarchical model proposed can provide accurate spatial interpolation and temporal aggregation by combining information from observed point‐referenced monitoring...

**Summary.**We analyse the shapes of star‐shaped objects which are prealigned. This is motivated from two examples studying the growth of leaves, and the temporal evolution of tree rings. In the latter case measurements were taken at fixed angles whereas in the former case the angles were free. Subsequently, this leads to different shape spaces, related to different concepts of size, for the analysis...

**Summary.**We propose an approach for estimating the date of lost confidence of jet engines, which are devices with multiple components subject to disruption. A mixed Weibull distribution is estimated from a large data set subject to censoring at various times. Parametric uncertainty is derived analytically and mapped visually onto the functions of use in reliability theory, including the hazard function...

**Summary.**Projections of future climate are often based on deterministic models of the Earth’s atmosphere and oceans. However, these projections can vary widely between models, with differences becoming more pronounced at the relatively fine spatial and temporal scales that are relevant in many applications. We suggest that the resulting uncertainty can be handled in a logically coherent and interpretable...

**Summary.**Fundamental frequency (F0, broadly ‘pitch’) is an integral part of spoken human language; however, a comprehensive quantitative model for F0 can be a challenge to formulate owing to the large number of effects and interactions between effects that lie behind the human voice's production of F0, and the very nature of the data being a contour rather than a point. The paper presents a semiparametric...

**Summary.**In dynamic models of infectious disease transmission, typically various mixing patterns are imposed on the so‐called ‘who acquires infection from whom’ matrix. These imposed mixing patterns are based on prior knowledge of age‐related social mixing behaviour rather than observations. Alternatively, we can assume that transmission rates for infections transmitted predominantly through non‐sexual...

**Summary.**Health economic decision models are subject to various forms of uncertainty, including uncertainty about the parameters of the model and about the model structure. These uncertainties can be handled within a Bayesian framework, which also allows evidence from previous studies to be combined with the data. As an example, we consider a Markov model for assessing the cost‐effectiveness of implantable...

**Summary.**Many popular estimators for duration models require independent competing risks or independent censoring. In contrast, copula‐based estimators are also consistent in the presence of dependent competing risks. We suggest a computationally convenient extension of the copula graphic estimator to a model with more than two dependent competing risks. We analyse the applicability of this estimator...

**Summary.**We analyse the effects of various treatments on cotton aphids (

*Aphis gossypii*). The standard analysis of count data on cotton aphids determines parameter values by assuming a deterministic growth model and combines these with the corresponding stochastic model to make predictions on population sizes, depending on treatment. Here, we use an integrated stochastic model to capture the intrinsic...

**Summary.**Racial disparities in risks of mortality adjusted for socio‐economic status are not well understood. To add to the understanding of racial disparities, we construct and analyse a data set that links, at individual and zip code levels, three government databases: Medicare, the Medicare Current Beneficiary Survey and US census. Our study population includes more than 4 million Medicare enrollees...