Estimating uncertainty of alcohol-attributable fractions for infectious and chronic diseases.

Background: Alcohol is a major risk factor for burden of disease and injuries globally. This paper presents a systematic method to compute the 95% confidence intervals of alcohol-attributable fractions (AAFs) with exposure and risk relations stemming from different sources.Methods: The computation was based on previous work done on modelling drinking prevalence using the gamma distribution and the inherent properties of this distribution. The Monte Carlo approach was applied to derive the variance for each AAF by generating random sets of all the parameters. A large number of random samples were thus created for each AAF to estimate variances. The derivation of the distributions of the different parameters is presented as well as sensitivity analyses which give an estimation of the number of samples required to determine the variance with predetermined precision, and to determine which parameter had the most impact on the variance of the AAFs.Results: The analysis of the five Asian regions showed that 150 000 samples gave a sufficiently accurate estimation of the 95% confidence intervals for each disease. The relative risk functions accounted for most of the variance in the majority of cases.Conclusions: Within reasonable computation time, the method yielded very accurate values for variances of AAFs.

Biplots of fuzzy coded data

A biplot, which is the multivariate generalization of the two-variable scatterplot, can be used to visualize the results of many multivariate techniques, especially those that are based on the singular value decomposition. We consider data sets consisting of continuous-scale measurements, their fuzzy coding and the biplots that visualize them, using a fuzzy version of multiple correspondence analysis. Of special interest is the way quality of fit of the biplot is measured, since it is well-known that regular (i.e., crisp) multiple correspondence analysis seriously under-estimates this measure. We show how the results of fuzzy multiple correspondence analysis can be defuzzified to obtain estimated values of the original data, and prove that this implies an orthogonal decomposition of variance. This permits a measure of fit to be calculated in the familiar form of a percentage of explained variance, which is directly comparable to the corresponding fit measure used in principal component analysis of the original data. The approach is motivated initially by its application to a simulated data set, showing how the fuzzy approach can lead to diagnosing nonlinear relationships, and finally it is applied to a real set of meteorological data.

Dynamic graphics of parametrically linked multivariate methods used in compositional data analysis

Many multivariate methods that are apparently distinct can be linked by introducing oneor more parameters in their definition. Methods that can be linked in this way arecorrespondence analysis, unweighted or weighted logratio analysis (the latter alsoknown as "spectral mapping"), nonsymmetric correspondence analysis, principalcomponent analysis (with and without logarithmic transformation of the data) andmultidimensional scaling. In this presentation I will show how several of thesemethods, which are frequently used in compositional data analysis, may be linkedthrough parametrizations such as power transformations, linear transformations andconvex linear combinations. Since the methods of interest here all lead to visual mapsof data, a "movie" can be made where where the linking parameter is allowed to vary insmall steps: the results are recalculated "frame by frame" and one can see the smoothchange from one method to another. Several of these "movies" will be shown, giving adeeper insight into the similarities and differences between these methods.

Trunk neuromuscular responses to a single whole-body vibration session in patients with chronic low back pain: a cross-sectional study.

OBJECTIVE: Whole-body vibration (WBV) exercise is progressively adopted as an alternative therapeutic modality for enhancing muscle force and muscle activity via neurogenic potentiation. So far, possible changes in the recruitment patterns of the trunk musculature after WBV remain undetermined. The main objective of this study was to evaluate the short-term effects of a single WBV session on trunk neuromuscular responses in patients with chronic low back pain (cLBP) and healthy participants. METHODS: Twenty patients with cLBP and 21 healthy participants performed 10 trunk flexion-extensions before and after a single WBV session consisting of five 1-minute vibration sets. Surface electromyography (EMG) of erector spinae at L2-L3 and L4-L5 and lumbopelvic kinematic variables were collected during the trials. Data were analyzed using 2-way mixed analysis of variance models. RESULTS: The WBV session led to increased lumbar EMG activity during the flexion and extension phases but yielded no change in the quiet standing and fully flexed phases. Kinematic data showed a decreased contribution to the movement of the lumbar region in the second extension quartile. These effects were not different between patients with cLBP and healthy participants. CONCLUSIONS: Increased lumbar EMG activity after a single WBV session most probably results from potentiation effects of WBV on lumbar muscles reflex responses. Decreased EMG activity in full trunk flexion, usually observed in healthy individuals, was still present after WBV, suggesting that the ability of the spine stabilizing mechanisms to transfer the extension torque from muscles to passive structures was not affected.

Breeding system and genetic variance in the monogamous, semi-social shrew, Crocidura russula

The population-genetic consequences of monogamy and male philopatry (a rare breeding system in mammals) were investigated using microsatellite markers in the semisocial and anthropophilic shrew Crocidura russula. A hierarchical sampling design over a 16-km geographical transect revealed a large genetic diversity (h = 0.813) with significant differentiation among subpopulations (F-ST = 5-6%), which suggests an exchange of 4.4 migrants per generation. Demic effective-size estimates were very high, due both to this limited gene inflow and to the inner structure of subpopulations. These were made of 13-20 smaller units (breeding groups), comprising an estimate of four breeding pairs each. Members of the same breeding groups displayed significant coancestries (F-LS = 9-10%), which was essentially due to strong male kinship: syntopic males were on average related at the half-sib level. Female dispersal among breeding groups was not complete (similar to 39%), and insufficient to prevent inbreeding. From our results, the breeding strategy of C. russula seems less efficient than classical mammalian systems (polygyny and male dispersal) in disentangling coancestry from inbreeding, but more so in retaining genetic variance.

Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

The application of NMR and MS methods for detection of adulteration of wine, fruit juices, and olive oil. A review

This review covers two important techniques, high resolution nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), used to characterize food products and detect possible adulteration of wine, fruit juices, and olive oil, all important products of the Mediterranean Basin. Emphasis is placed on the complementary use of SNIF-NMR (site-specific natural isotopic fractionation nuclear magnetic resonance) and IRMS (isotope-ratio mass spectrometry) in association with chemometric methods for detecting the adulteration.

Inference with the lognormal distribution

Several estimators of the expectation, median and mode of the lognormal distribution are derived. They aim to be approximately unbiased, efficient, or have a minimax property in the class of estimators we introduce. The small-sample properties of these estimators are assessed by simulations and, when possible, analytically. Some of these estimators of the expectation are far more efficient than the maximum likelihood or the minimum-variance unbiased estimator, even for substantial samplesizes.

An empirical evaluation of small area estimators

This paper investigates the comparative performance of five small areaestimators. We use Monte Carlo simulation in the context of boththeoretical and empirical populations. In addition to the direct andindirect estimators, we consider the optimal composite estimator withpopulation weights, and two composite estimators with estimatedweights: one that assumes homogeneity of within area variance andsquare bias, and another one that uses area specific estimates ofvariance and square bias. It is found that among the feasibleestimators, the best choice is the one that uses area specificestimates of variance and square bias.

Heidelberg Retina Tomograph in Glaucoma Case-finding

Purpose: To compare the disease classification using optic nerve head imaging against clinical examination combined with perimetry in the case-finding environment.Methods: During a glaucoma screening event at the University Hospital in Lausanne 148 attendees opted to undergo an extended screening exam consisting of perimetry with Octopus (Haag-Streit, Koeniz, Switzerland), tonometry, gonioscopy, slit-lamp optic nerve head examination and Heidelberg Retinal Tomorgraph (HRT, Heidelberg engineering). Classification criteria of an abnormal clinical exam consisted of a cup to disc ratio > 0.6, other disc abnormality (e.g. notching), closed angles, Van Herrick < ¼ and intraocular pressure >21mmHg. In perimetry a square root loss variance (sLV) >3.0 dB was considered abnormal. Those cases with both an abnormal clinical exam and abnormal perimetric results were considered to be glaucoma suspects. An abnormal HRT exam was a global Moorfields Regression Analysis (MRA) result of "outside normal limits". The results from the worse eye for each instrument are reported.Results: The mean age of the patients was 59.9 years (SD ±14.8years). 46 subjects failed the clinical exam. 55 subjects had sLV>3.0dB. 86 subjects failed one or more of the testing components, 21 subjects failed both the clinical exam and perimetry. Two cases of advanced glaucoma were diagnosed on the day of the event. 20 subjects were referred due to other ocular pathology (10 cataract; 2 AMD; 8 other). 16 subjects were outside normal limits with the HRT, of which 11 failed the clinical exam, 9 failed the perimetric exam and 7 failed all three. HRT had a sensitivity of 33% CI [15%,57%] with a specificity of 93% CI [87%,97%].Conclusions: HRT shows good specificity, however the low sensitivity makes it of limited use in the proposed case finding scenario.

Portfolio choice beyond the traditional approach

This paper surveys asset allocation methods that extend the traditional approach. An important feature of the the traditional approach is that measures the risk and return tradeoff in terms of mean and variance of final wealth. However, there are also other important features that are not always made explicit in terms of investor s wealth, information, and horizon: The investor makes a single portfolio choice based only on the mean and variance of her final financial wealth and she knows the relevant parameters in that computation. First, the paper describes traditional portfolio choice based on four basic assumptions, while the rest of the sections extend those assumptions. Each section will describe the corresponding equilibrium implications in terms of portfolio advice and asset pricing.

Estimates of patient costs related with population morbidity: Can indirect costs affect the results?

A number of health economics works require patient cost estimates as a basic information input.However the accuracy of cost estimates remains in general unspecified. We propose to investigate howthe allocation of indirect costs or overheads can affect the estimation of patient costs in order to allow forimprovements in the analysis of patient costs estimates. Instead of focusing on the costing method, thispaper proposes to highlight changes in variance explained observed when a methodology is chosen. Wecompare three overhead allocation methods for a specific Spanish population adjusted using the ClinicalRisk Groups (CRG), and we obtain different series of full-cost group estimates. As a result, there aresignificant gains in the proportion of the variance explained, depending upon the methodology used.Furthermore, we find that the global amount of variation explained by risk adjustment models dependsmainly on direct costs and is independent of the level of aggregation used in the classification system.

Comparison of potential adjustment variables representing primary intellectual level in epidemiological studies on neurotoxicity

BACKGROUND: Primary intellectual abilities (PIA) are a confounder in epidemiological studies on neurotoxicity. A good measure of this confounder should be independent of age as PIA is an intrinsic ability. Furthermore, as PIA is related to health endpoints, any measure of PIA should reveal this association. This study is aimed at comparing vocabulary test, diploma and age at end of schooling properties as measures of PIA in a non-exposed population of workers. METHODS: The design was a cross-sectional study of 413 non-exposed workers (203 women and 210 men) selected from a health check-up center. The effect of age on the vocabulary score was assessed using an analysis of covariance adjusted for diploma. Relationships between neuropsychological performances and vocabulary score, diploma and end of schooling age were, respectively, assessed using multiple linear regressions adjusted for age and gender. RESULTS: Vocabulary score increased significantly with age, both for men and women. The increase was 0.14 word per year for women, and 0.18 word per year for men. The explained variance of the models evaluating the relationships between age at end of schooling, diploma, vocabulary test, and neuropsychological performances was quite similar for the three measures of PIA. CONCLUSIONS: Vocabulary score was found to be age-related, even after adjustment for diploma. No difference was found between these three variables in terms of their relationship to neuropsychological endpoints. Moreover, the literature shows that vocabulary test performances are influenced by exposure to neurotoxic agents. These results suggest that vocabulary score could be of interest for participants of similar ages and similar diplomas. Otherwise, the other two variables would be better PIA measures in neurotoxicology studies.

Design effect and interviewer effects: Evidence from the Spanish ESS3-2006 Data

In 2007 the first Quality Enhancement Meeting on sampling in the European SocialSurvey (ESS) took place. The discussion focused on design effects and inteviewereffects in face-to-face interviews. Following the recomendations of this meeting theSpanish ESS team studied the impact of interviewers as a new element in the designeffect in the response s variance using the information of the correspondent SampleDesign Data Files. Hierarchical multilevel and cross-classified multilevel analysis areconducted in order to estimate the amount of responses variation due to PSU and tointerviewers for different questions in the survey. Factor such as the age of theinterviewer, gender, workload, training and experience and respondent characteristicssuch as age, gender, renuance to participate and their possible interactions are alsoincluded in the analysis of some specific questions like trust in politicians and trustin legal system . Some recomendations related to future sampling designs and thecontents of the briefing sessions are derived from this initial research.

Duality in mean-variance frontiers with conditioning information

Portfolio and stochastic discount factor (SDF) frontiers are usually regarded as dual objects, and researchers sometimes use one to answer questions about the other. However, the introduction of conditioning information and active portfolio strategies alters this relationship. For instance, the unconditional portfolio frontier in Hansen and Richard (1987) is not dual to the unconditional SDF frontier in Gallant, Hansen and Tauchen (1990). We characterise the dual objects to those frontiers, and relate them to the frontiers generated with managed portfolios, which are commonly used in empirical work. We also study the implications of a safe asset and other special cases.