Nonparametric Estimation of Data Dimensionality Prior to Data Compression: the case of the Human Development Index

In many applications in applied statistics researchers reduce the complexity of a data set by combining a group of variables into a single measure using factor analysis or an index number. We argue that such compression loses information if the data actually has high dimensionality. We advocate the use of a non-parametric estimator, commonly used in physics (the Takens estimator), to estimate the correlation dimension of the data prior to compression. The advantage of this approach over traditional linear data compression approaches is that the data does not have to be linearized. Applying our ideas to the United Nations Human Development Index we find that the four variables that are used in its construction have dimension three and the index loses information.

Laughter Induction Techniques Suitable for Generating Motion Capture Data of Laughter Associated Body Movements

Laughter is a frequently occurring social signal and an important part of human non-verbal communication. However it is often overlooked as a serious topic of scientific study. While the lack of research in this area is mostly due to laughter’s non-serious nature, it is also a particularly difficult social signal to produce on demand in a convincing manner; thus making it a difficult topic for study in laboratory settings. In this paper we provide some techniques and guidance for inducing both hilarious laughter and conversational laughter. These techniques were devised with the goal of capturing mo- tion information related to laughter while the person laughing was either standing or seated. Comments on the value of each of the techniques and general guidance as to the importance of atmosphere, environment and social setting are provided.

External beam radiotherapy in exudative age-related macular degeneration: a pooled analysis of phase I data

In recent years external beam radiotherapy (EBRT) has been proposed as a treatment for the wet form of age-related macular degeneration (AMD) where choroidal neovascularization (CNV) is the hallmark. While the majority of pilot (Phase I) studies have reported encouraging results, a few have found no benefit, i.e. EBRT was not found to result in either improvement or stabilization of visual acuity of the treated eye. The natural history of visual loss in untreated CNV of AMD is highly variable. Loss of vision is influenced mainly by the presenting acuity, and size and composition of the lesion, and to a lesser extent by a variety of other factors. Thus the variable outcome reported by the small Phase I studies of EBRT published to date may simply reflect the variation in baseline factors. We therefore obtained information on 409 patients treated with EBRT from eight independent centres, which included details of visual acuity at baseline and at subsequent follow-up visits. Analysis of the data showed that 22.5% and 14.9% of EBRT-treated eyes developed moderate and severe loss of vision, respectively, during an average follow-up of 13 months. Initial visual acuity, which explained 20.5% of the variation in visual loss, was the most important baseline factor studied. Statistically significant differences in loss of vision were observed between centres, after considering the effects of case mix factors. Comparisons with historical data suggested that while moderate visual loss was similar to that of the natural history of the disease, the likelihood of suffering severe visual loss was halved. However, the benefit in terms of maintained/improved vision in the treated eye was modest.

Psychotropic medications and the transition into care:a national data linkage study

Objectives
To determine whether excessive and often inappropriate or dangerous psychotropic drug dispensing to older adults is unique to care homes or is a continuation of community treatment.

Design
Population-based data-linkage study using prescription drug information.

Setting
Northern Ireland's national prescribing database and care home information from the national inspectorate.

Participants
Two hundred fifty thousand six hundred seventeen individuals aged 65 and older.

Measurements
Prescription information was extracted for all psychotropic drugs included in the British National Formulary (BNF) categories 4.1.1, 4.1.2, and 4.2.2 (hypnotics, anxiolytics, and antipsychotics) dispensed over the study period. Repeated cross-sectional analysis was used to monitor changes in psychotropic drug dispensing over time.

Results
Psychotropic drug use was higher in care homes than the community; 20.3% of those in care homes were dispensed an antipsychotic in January 2009, compared with 1.1% of those in the community. People who entered care had higher use of psychotropic medications before entry than those who did not enter care, but this increased sharply in the month of admission and continued to rise. Antipsychotic drug dispensing increased from 8.2% before entry to 18.6% after entering care (risk ratio (RR) = 2.26, 95% confidence interval (CI)=1.96–2.59) and hypnotic drug dispensing from 14.8% to 26.3% (RR=1.78, 95% CI=1.61–1.96).

Conclusion
A continuation of high use before entry cannot wholly explain the higher dispensing of psychotropic drugs to individuals in care homes. Although drug dispensing is high in older people in the community, it increases dramatically on entry to care. Routine medicine reviews are necessary in older people and are especially important during transitions of care.

Changing attitudes to gender roles: A longitudinal analysis of ordinal response data from the British household panel study

This article examines changes in attitudes to gender roles in contemporary Britain by using a first-order Markov process in which cumulative transition probabilities are logistic functions of a set of personal and socioeconomic characteristics of respondents. The data are taken from the British Household Panel Study (BHPS). The attitudinal responses examined take the form of ordinal responses concerning gender roles in 1991 and 2003. The likelihood function is partitioned to make possible the use of existing software for estimating model parameters. For the BHPS data, it was found that, depending on the value of the response in 1991, a variety of factors were important determinants of attitudes to gender roles by 2003.

Robust Multimodal Person Identification With Limited Training Data

This paper presents a novel method of audio-visual feature-level fusion for person identification where both the speech and facial modalities may be corrupted, and there is a lack of prior knowledge about the corruption. Furthermore, we assume there are limited amount of training data for each modality (e.g., a short training speech segment and a single training facial image for each person). A new multimodal feature representation and a modified cosine similarity are introduced to combine and compare bimodal features with limited training data, as well as vastly differing data rates and feature sizes. Optimal feature selection and multicondition training are used to reduce the mismatch between training and testing, thereby making the system robust to unknown bimodal corruption. Experiments have been carried out on a bimodal dataset created from the SPIDRE speaker recognition database and AR face recognition database with variable noise corruption of speech and occlusion in the face images. The system's speaker identification performance on the SPIDRE database, and facial identification performance on the AR database, is comparable with the literature. Combining both modalities using the new method of multimodal fusion leads to significantly improved accuracy over the unimodal systems, even when both modalities have been corrupted. The new method also shows improved identification accuracy compared with the bimodal systems based on multicondition model training or missing-feature decoding alone.

An Examination of Transformation Techniques to Investigate and Interpret Multivariate Geochemical Data Analysis: Tellus Case Study

This research aims to use the multivariate geochemical dataset, generated by the Tellus project, to investigate the appropriate use of transformation methods to maintain the integrity of geochemical data and inherent constrained behaviour in multivariate relationships. The widely used normal score transform is compared with the use of a stepwise conditional transform technique. The Tellus Project, managed by GSNI and funded by the Department of Enterprise Trade and Development and the EU’s Building Sustainable Prosperity Fund, involves the most comprehensive geological mapping project ever undertaken in Northern Ireland. Previous study has demonstrated spatial variability in the Tellus data but geostatistical analysis and interpretation of the datasets requires use of an appropriate methodology that reproduces the inherently complex multivariate relations. Previous investigation of the Tellus geochemical data has included use of Gaussian-based techniques. However, earth science variables are rarely Gaussian, hence transformation of data is integral to the approach. The multivariate geochemical dataset generated by the Tellus project provides an opportunity to investigate the appropriate use of transformation methods, as required for Gaussian-based geostatistical analysis. In particular, the stepwise conditional transform is investigated and developed for the geochemical datasets obtained as part of the Tellus project. The transform is applied to four variables in a bivariate nested fashion due to the limited availability of data. Simulation of these transformed variables is then carried out, along with a corresponding back transformation to original units. Results show that the stepwise transform is successful in reproducing both univariate statistics and the complex bivariate relations exhibited by the data. Greater fidelity to multivariate relationships will improve uncertainty models, which are required for consequent geological, environmental and economic inferences.

The effects of climate change on ovine parasitic gastroenteritis determined using veterinary surveillance and meteorological data for Northern Ireland over the period 1999-2009

While the influence of temperature and moisture on the free-living stages of gastrointestinal nematodes have been described in detail, and evidence for global climate change is mounting, there have been only a few attempts to relate altered incidence or seasonal patterns of disease to climate change. Studies of this type have been completed for England Scotland and Wales, but not for Northern Ireland (NI). Here we present an analysis of veterinary diagnostic data that relates three categories of gastrointestinal nematode infection in sheep to historical meteorological data for NI. The infections are: trichostrongylosis/teladorsagiosis (Teladorsagia/Trichostrongylus), strongyloidosis and nematodirosis. This study aims to provide a baseline for future climate change analyses and to provide basic information for the development of nematode control programmes. After identifying and evaluating possible sources of bias, climate change was found to be the most likely explanation for the observed patterns of change in parasite epidemiology, although other hypotheses could not be refuted. Seasonal rates of diagnosis showed a uniform year-round distribution for Teladorsagia and Trichostrongylus infections, suggesting consistent levels of larval survival throughout the year and extension of the traditionally expected seasonal transmission windows. Nematodirosis showed a higher level of autumn than Spring infection, suggesting that suitable conditions for egg and larval development occurred after the Spring infection period. Differences between regions within the Province were shown for strongyloidosis, with peaks of infection falling in the period September-November. For all three-infection categories (trichostrongylosis/teladorsagiosis, strongyloidosis and nematodirosis), significant differences in the rates of diagnosis, and in the seasonality of disease, were identified between regions. (C) 2012 Elsevier B.V. All rights reserved.

Collective Participation Impacts Social Identity::A Longitudinal Study with Control Data

How does participation in collective activity affect our social identifications and behavior? We investigate this question in a longitudinal questionnaire study conducted at one of the world’s largest collective events – the Magh Mela (a month-long Hindu religious festival in north India). Data gathered from pilgrims and comparable others who did not attend the event show that one month after this mass gathering was over, those who had participated (but not controls) exhibited a heightened social identification as Hindu and increased levels of religious activity (e.g., performing prayer rituals). Additional data gathered from the pilgrim respondents during the festival show that the pilgrims’ perceptions of sharing a common identity with other pilgrims, and of being able to enact their social identity in this event, predicted these outcomes.