Some last thoughts on compositional data analysis

One of the disadvantages of old age is that there is more past than future: this,however, may be turned into an advantage if the wealth of experience and, hopefully,wisdom gained in the past can be reflected upon and throw some light on possiblefuture trends. To an extent, then, this talk is necessarily personal, certainly nostalgic,but also self critical and inquisitive about our understanding of the discipline ofstatistics. A number of almost philosophical themes will run through the talk: searchfor appropriate modelling in relation to the real problem envisaged, emphasis onsensible balances between simplicity and complexity, the relative roles of theory andpractice, the nature of communication of inferential ideas to the statistical layman, theinter-related roles of teaching, consultation and research. A list of keywords might be:identification of sample space and its mathematical structure, choices betweentransform and stay, the role of parametric modelling, the role of a sample spacemetric, the underused hypothesis lattice, the nature of compositional change,particularly in relation to the modelling of processes. While the main theme will berelevance to compositional data analysis we shall point to substantial implications forgeneral multivariate analysis arising from experience of the development ofcompositional data analysis…

L'enseignement du patient diabétique et son évaluation par un questionnaire à choix multiple. [Education of the diabetic patient and its evaluation by a multiple-choice questionnaire].

37 insulin-dependent and non-insulin-dependent diabetics answered a multiple-choice questionnaire during inpatient educational sessions. 12 dietetic and 12 pathophysiologic questions had to be answered. Statistical analysis of factors influencing the number of errors can be summed up as follows: there is a direct correlation between age of the patient and number of errors; the older the patient, the greater the number of errors. However, insulin-dependent diabetics committed fewer errors than non-insulin-dependent subjects of the same age, which suggests greater motivation in the first group due to their treatment. The test likewise affords the patients an opportunity of reviewing unclear topics and enables the educational team to adapt their teaching to the patients.

The control of hypertension in men and women: a comparative analysis

Abstract OBJECTIVE To compare men and women who have hypertension with reference to the following: high blood pressure, biosocial variables, habits and life styles, mental disorders, and social support networks. METHOD 290 hypertensive patients (women, 62.1%) were evaluated. The assessments involved the following: measuring blood pressure with an automatic measuring device, evaluating social status through the Social Support Scale, and the use of a Self-Report Questionnaire (SRQ-20) to identify common mental disorders. A value of p<0.05 was considered statistically significant. RESULTS Women were found to be different to men (p<0.05) in the following areas having: better control of their blood pressure (64.4% vs 52.7%), less salary incomes, less diabetes, higher total cholesterol, higher body mass index and wider abdominal circumferences. They also had lower systolic blood pressure, lower levels of alcohol consumption and a greater prevalence for mental disorders. The social support assessment revealed that hypertensive women received less help with preparing meals but had more company from people which allowed them to engage in enjoyable activities. CONCLUSION Women had more control over their blood pressure than men, despite the presence of negative biopsychosocial factors that may have influenced their adherence to the treatments.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Physical activity assessment using a pedometer and its comparison with a questionnaire in a large population survey.

The aim of this study was to evaluate the use of the pedometer in epidemiologic research on physical activity. Within the framework of a health examination survey in 1988-1989, physical activity was assessed in a representative population sample of 493 men and women aged 25-74 years who were residents of Switzerland. They wore a pedometer for 1 week at work and during leisure time, and the results, converted into steps per day, were compared with answers to a questionnaire. The average number of steps per day decreased from 11,900 to 6,700 and from 9,300 to 7,300 for men and women, respectively, in the youngest to the oldest age groups. For men, categorized according to type of physical activity at work, there was a highly significant difference in the number of steps (p < 0.001), whereas in women the results were associated with leisure-time physical activity (p = 0.003). For both sexes, practicing sports more than once a week was associated with an important increase in steps per day. Analyzing the number of steps according to the day of the week and occupational category produced an unexpected result: Men with a physically active job engaged in more leisure-time physical activity on the weekend. The pedometer proved to be useful in assessing physical activity in a large, free-living population.

Factor structure of the SOCRATES questionnaire in hospitalized medical patients.

The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES), a 19-item instrument developed to assess readiness to change alcohol use among individuals presenting for specialized alcohol treatment, has been used in various populations and settings. Its factor structure and concurrent validity has been described for specialized alcohol treatment settings and primary care. The purpose of this study was to determine the factor structure and concurrent validity of the SOCRATES among medical inpatients with unhealthy alcohol use not seeking help for specialized alcohol treatment. The subjects were 337 medical inpatients with unhealthy alcohol use, identified during their hospital stay. Most of them had alcohol dependence (76%). We performed an Alpha Factor Analysis (AFA) and Principal Component Analysis (PCA) of the 19 SOCRATES items, and forced 3 factors and 2 components, in order to replicate findings from Miller and Tonigan (Miller, W. R., & Tonigan, J. S., (1996). Assessing drinkers' motivations for change: The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES). Psychology of Addictive Behavior, 10, 81-89.) and Maisto et al. (Maisto, S. A., Conigliaro, J., McNeil, M., Kraemer, K., O'Connor, M., & Kelley, M. E., (1999). Factor structure of the SOCRATES in a sample of primary care patients. Addictive Behavior, 24(6), 879-892.). Our analysis supported the view that the 2 component solution proposed by Maisto et al. (Maisto, S.A., Conigliaro, J., McNeil, M., Kraemer, K., O'Connor, M., & Kelley, M.E., (1999). Factor structure of the SOCRATES in a sample of primary care patients. Addictive Behavior, 24(6), 879-892.) is more appropriate for our data than the 3 factor solution proposed by Miller and Tonigan (Miller, W. R., & Tonigan, J. S., (1996). Assessing drinkers' motivations for change: The Stages of Change Readiness and Treatment Eagerness Scale (SOCRATES). Psychology of Addictive Behavior, 10, 81-89.). The first component measured Perception of Problems and was more strongly correlated with severity of alcohol-related consequences, presence of alcohol dependence, and alcohol consumption levels (average number of drinks per day and total number of binge drinking days over the past 30 days) compared to the second component measuring Taking Action. Our findings support the view that the SOCRATES is comprised of two important readiness constructs in general medical patients identified by screening.

Automatic classification of MR scans in Alzheimer's disease.

To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

Data-based approach for developing a physical activity frequency questionnaire.

Measurement of total energy expenditure may be crucial to an understanding of the relation between physical activity and disease and in order to frame public health intervention. To devise a self-administered physical activity frequency questionnaire (PAFQ), the following data-based approach was used. A 24-hour recall was administered to a random sample of 919 adult residents of Geneva, Switzerland. The data obtained were used to establish the list of activities (and their median duration) that contributed to 95% of the energy expended, separately for men and women. Activities that were trivial for the whole sample but that contributed to > or = 10% of an individual's energy expenditure were also selected. The final PAFQ lists 70 activities or group of activities with their typical duration. About 20 minutes are required for respondents to indicate the number of days and the number of hours per day that they performed each activity. The PAFQ method was validated against a heart rate monitor, a more objective method. The total energy estimated by the PAFQ in 41 volunteers correlated well (r = 0.76) with estimates using a heart rate monitor. The authors conclude that the design of their self-administered physical activity frequency questionnaire based on data from 24-hour recall appeared to accurately estimate energy expenditure.

Subset correspondence analysis: Visualizing relationships among a selected set of response categories from a questionnaire survey

It is shown how correspondence analysis may be applied to a subset of response categories from a questionnaire survey, for example the subset of undecided responses or the subset of responses for a particular category. The idea is to maintain the original relative frequencies of the categories and not re-express them relative to totals within the subset, as would normally be done in a regular correspondence analysis of the subset. Furthermore, the masses and chi-square metric assigned to the data subset are the same as those in the correspondence analysis of the whole data set. This variant of the method, called Subset Correspondence Analysis, is illustrated on data from the ISSP survey on Family and Changing Gender Roles.

Reproductibilité et discussion des différents biais d'un questionnaire de fréquence alimentaire adapté à une population de femmes suisses âgées (>75ans)

Résumé: Un des domaines de prédilection de la recherche préventive en ostéoporose, est l'alimentation. L'étude « EVANIBUS » s'inscrit dans le cadre de cette recherche. Un de ses buts est de cibler à travers un questionnaire de fréquence alimentaire chez une population féminine âgée de plus de 75 ans, l'alimentation à risque pour l'ostéoporose. Le choix du questionnaire pour cette étude s'est porté sur le «Food Frequency Questionnaire», élaboré et validé sur une population pré-ménopausique écossaise par Susan New. Ce questionnaire se répartit en différents groupes et sous-groupes alimentaires. A l'aide de tables nutritionnelles les principaux micronutriments essentiels à la santé osseuse contenus dans lés sous-groupes alimentaires ont été calculés. Avant d'utiliser un questionnaire de fréquence alimentaire dans une population différente, il est nécessaire de procéder à une adaptation et une nouvelle validation du questionnaire. Cependant, cette procédure nécessite la collaboration d'un spécialiste en nutrition. Pour cette raison, seule la reproductibilité du questionnaire a été testée. Le test choisi est la première et deuxième étape du test de Bland-Altman. La reproductibilité s'établit entre les 2 mesures (1 mois d'intervalle) de la fréquence moyenne de consommation obtenue pour chaque item (groupes et sous-groupes alimentaires). Les résultats montrent que seule une minorité d'item présente une acceptation des 2 étapes du test de Bland-Altman. Pour expliquer cette mauvaise reproductibilité, les biais systématiques ont été mis en évidence et analysés en détails. Les erreurs dues à la méthodologie sont également analysées. Ces dernières sont en principe évitables. C'est l'absence d'adaptation du questionnaire qui semble en être la cause principale. A cet effet des mesures de correction sont proposées, telles qu'un pilotage du questionnaire dans un échantillon de la population cible. L'analyse du questionnaire relève également une diminution globale de la consommation lors de la deuxième mesure. On émet alors, l'hypothèse d'une influence météorologique par l'intermédiaire d'une hausse des températures.