Marian Scott

Pain assessment in animals

Attitudes to pain in animals have changed dramatically over the past two decades, with marked advances in its treatment. However, while the importance of measuring animal pain in a valid and reliable manner has been acknowledged for some time, veterinary scientists have been slow to recognise the important contribution of the psychometric approach to the construction of measurement instruments. Well established in human medicine, psychometric methods, which ensure that the end product is valid, reliable and, where required, responsive to clinical change, are the ‘gold standard’ in instrument design. In addition to discussing the particular challenges veterinary scientists face when designing instruments to measure pain in animals, this article describes the psychometric approach and, using the dog as an example, demonstrates how this approach can be used to produce scientifically robust pain scales for non-human species.

A comparison of clustering approaches for the study of the temporal coherence of multiple time series

Two approaches for clustering of time series have been considered. The first is a novel approach based on a modification of classic state-space modelling while the second is based on functional clustering. For the latter, both k-means and complete-linkage hierarchical clustering algorithms are adopted. The two approaches are compared using a simulation study, and are applied to lake surface water temperature for 256 lakes globally for 5 years of data, to investigate information obtained from each approach.

Language impairment and aggression in Alzheimer's disease

The opportunity, in a drug study of Alzheimers disease, is taken to explore the association of aggression and cognitive impairment. This is an important association to explore in its own right. However, in view of the increasing age of the population and the particular problems aggression poses for carers, any association of aggression with cognitive impairment assumes particular importance. A marked association of language impairment with aggression is demonstrated (Spearman R = − 0.735, p = 0.0005, N = 18).

An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: a case study of nitrogen dioxide concentrations in Scotland

The long-term health effects of air pollution can be estimated using a spatio-temporal ecological study, where the disease data are counts of hospital admissions from populations in small areal units at yearly intervals. Spatially representative pollution concentrations for each areal unit are typically estimated by applying Kriging to data from a sparse monitoring network, or by computing averages over grid level concentrations from an atmospheric dispersion model. We propose a novel fusion model for estimating spatially aggregated pollution concentrations using both the modelled and monitored data, and relate these concentrations to respiratory disease in a new study in Scotland between 2007 and 2011.

Statistics: more than pictures

This, the third of our series of articles on statistics in veterinary medicine, moves onto the more complex concepts of hypothesis testing and confidence intervals. As these two areas are widely discussed in many clinical research publications, an awareness of the underlying methodology behind their use is essential to appreciate the information they convey.

Statistics: dealing with categorical data

This, the fifth of our series of articles on statistics in veterinary medicine, moves onto modelling categorical data, in particular assessing associations between variables. Some of the questions we shall consider are widely discussed in many clinical research publications, and we will use the ideas of hypothesis tests and confidence intervals to answer those questions.

Challenges in modeling detailed and complex environmental data sets: a case study modeling the excess partial pressure of fluvial \hbox {CO}_2

Advances in sensor technology enable environmental monitoring programmes to record and store measurements at a high temporal resolution, enhancing the capacity to detect and understand short duration changes that would not have been apparent in the past with monthly, fortnightly or even daily sampling. However, there are various challenges in terms of the processing and analysis of these environmental high-frequency data due to their complex behavior over the different timescales and the strong correlation structure that persists over a large number of lags. Here, we explore the complexities of modeling high-frequency data which arise from environmental applications. With increasing understanding of the importance of surface waters as a source of atmospheric

An evaluation of a target-controlled infusion of propofol or propofol-alfentanil admixture for sedation in dogs.

\hbox {CO}_2