Stepwise multiple testing as formalized data snooping

It is common in econometric applications that several hypothesis tests arecarried out at the same time. The problem then becomes how to decide whichhypotheses to reject, accounting for the multitude of tests. In this paper,we suggest a stepwise multiple testing procedure which asymptoticallycontrols the familywise error rate at a desired level. Compared to relatedsingle-step methods, our procedure is more powerful in the sense that itoften will reject more false hypotheses. In addition, we advocate the useof studentization when it is feasible. Unlike some stepwise methods, ourmethod implicitly captures the joint dependence structure of the teststatistics, which results in increased ability to detect alternativehypotheses. We prove our method asymptotically controls the familywise errorrate under minimal assumptions. We present our methodology in the context ofcomparing several strategies to a common benchmark and deciding whichstrategies actually beat the benchmark. However, our ideas can easily beextended and/or modied to other contexts, such as making inference for theindividual regression coecients in a multiple regression framework. Somesimulation studies show the improvements of our methods over previous proposals. We also provide an application to a set of real data.

Fusion of data sets in multivariate linear regression with errors-in-variables

We consider the application of normal theory methods to the estimation and testing of a general type of multivariate regressionmodels with errors--in--variables, in the case where various data setsare merged into a single analysis and the observable variables deviatepossibly from normality. The various samples to be merged can differ on the set of observable variables available. We show that there is a convenient way to parameterize the model so that, despite the possiblenon--normality of the data, normal--theory methods yield correct inferencesfor the parameters of interest and for the goodness--of--fit test. Thetheory described encompasses both the functional and structural modelcases, and can be implemented using standard software for structuralequations models, such as LISREL, EQS, LISCOMP, among others. An illustration with Monte Carlo data is presented.

High capacity robust audio watermarking scheme based on FFT and linear regression

Peer-reviewed

Polyphenol-rich foods in the Mediterranean diet are associated with better cognitive function in elderly subjects at high cardiovascular risk

Brain oxidative processes play a major role in age-related cognitive decline, thus consumption of antioxidant-rich foods might help preserve cognition. Our aim was to assess whether consumption of antioxidant-rich foods in the Mediterranean diet relates to cognitive function in the elderly. In asymptomatic subjects at high cardiovascular risk (n = 447; 52% women; age 5580 y) enrolled in the PREDIMED study, a primary prevention dietary-intervention trial, we assessed food intake and cardiovascular risk profile, determined apolipoprotein E genotype, and used neuropsychological tests to evaluate cognitive function.We also measured urinary polyphenols as an objective biomarker of intake. Associations between energy-adjusted food consumption, urinary polyphenols, and cognitive scores were assessed by multiple linear regression models adjusted for potential confounders. Consumption of some foods was independently related to better cognitive function. The specific associations [regression coefficients (95% confidence intervals)] were: total olive oil with immediate verbal memory [0.755 (0.1511.358)]; virgin olive oil and coffee with delayed verbal memory [0.163 (0.0100.316) and 0.294 (0.0550.534), respectively];walnuts with working memory [1.191 (0.0612.322)]; and wine with Mini-Mental State Examination scores [0.252 (0.0060.496)]. Urinary polyphenols were associated with better scores in immediate verbal memory [1.208 (0.2362.180)]. Increased consumption of antioxidant-rich foods in general and of polyphenols in particular is associated with better cognitive performance in elderly subjects at high cardiovascular risk. The results reinforce the notion that Mediterranean diet components might counteract age-related cognitive decline.

Polyphenol-rich foods in the Mediterranean diet are associated with better cognitive function in elderly subjects at high cardiovascular risk

Brain oxidative processes play a major role in age-related cognitive decline, thus consumption of antioxidant-rich foods might help preserve cognition. Our aim was to assess whether consumption of antioxidant-rich foods in the Mediterranean diet relates to cognitive function in the elderly. In asymptomatic subjects at high cardiovascular risk (n = 447; 52% women; age 55-80 y) enrolled in the PREDIMED study, a primary prevention dietary-intervention trial, we assessed food intake and cardiovascular risk profile, determined apolipoprotein E genotype, and used neuropsychological tests to evaluate cognitive function.We also measured urinary polyphenols as an objective biomarker of intake. Associations between energy-adjusted food consumption, urinary polyphenols, and cognitive scores were assessed by multiple linear regression models adjusted for potential confounders. Consumption of some foods was independently related to better cognitive function. The specific associations [regression coefficients (95% confidence intervals)] were: total olive oil with immediate verbal memory [0.755 (0.151-1.358)]; virgin olive oil and coffee with delayed verbal memory [0.163 (0.010-0.316) and 0.294 (0.055-0.534), respectively];walnuts with working memory [1.191 (0.061-2.322)]; and wine with Mini-Mental State Examination scores [0.252 (0.006-0.496)]. Urinary polyphenols were associated with better scores in immediate verbal memory [1.208 (0.236-2.180)]. Increased consumption of antioxidant-rich foods in general and of polyphenols in particular is associated with better cognitive performance in elderly subjects at high cardiovascular risk. The results reinforce the notion that Mediterranean diet components might counteract age-related cognitive decline.

A short screener is valid for assessing mediterranean diet adherence among older spanish men and women

Ensuring the accuracy of dietary assessment instruments is paramount for interpreting diet-disease relationships. The present study assessed the relative and construct validity of the 14-point Mediterranean Diet Adherence Screener (MEDAS) used in the Prevencio´n con Dieta Mediterra´nea (PREDIMED) study, a primary prevention nutrition-intervention trial. A validated FFQ and the MEDAS were administered to 7146 participants of the PREDIMED study. The MEDASderived PREDIMED score correlated significantly with the corresponding FFQ PREDIMED score (r = 0.52; intraclass correlation coefficient = 0.51) and in the anticipated directions with the dietary intakes reported on the FFQ. Using Bland Altman"s analysis, the average MEDAS Mediterranean diet score estimate was 105% of the FFQ PREDIMED score estimate. Limits of agreement ranged between 57 and 153%. Multiple linear regression analyses revealed that a higher PREDIMED score related directly (P , 0.001) to HDL-cholesterol (HDL-C) and inversely (P , 0.038) to BMI, waist circumference, TG, the TG:HDL-C ratio, fasting glucose, and the cholesterol:HDL-C ratio. The 10-y estimated coronary artery disease risk decreased as the PREDIMED score increased (P , 0.001). The MEDAS is a valid instrument for rapid estimation of adherence to the Mediterranean diet and may be useful in clinical practice.

A short screener is valid for assessing mediterranean diet adherence among older spanish men and women

Ensuring the accuracy of dietary assessment instruments is paramount for interpreting diet-disease relationships. The present study assessed the relative and construct validity of the 14-point Mediterranean Diet Adherence Screener (MEDAS) used in the Prevencio´n con Dieta Mediterra´nea (PREDIMED) study, a primary prevention nutrition-intervention trial. A validated FFQ and the MEDAS were administered to 7146 participants of the PREDIMED study. The MEDASderived PREDIMED score correlated significantly with the corresponding FFQ PREDIMED score (r = 0.52; intraclass correlation coefficient = 0.51) and in the anticipated directions with the dietary intakes reported on the FFQ. Using Bland Altman"s analysis, the average MEDAS Mediterranean diet score estimate was 105% of the FFQ PREDIMED score estimate. Limits of agreement ranged between 57 and 153%. Multiple linear regression analyses revealed that a higher PREDIMED score related directly (P , 0.001) to HDL-cholesterol (HDL-C) and inversely (P , 0.038) to BMI, waist circumference, TG, the TG:HDL-C ratio, fasting glucose, and the cholesterol:HDL-C ratio. The 10-y estimated coronary artery disease risk decreased as the PREDIMED score increased (P , 0.001). The MEDAS is a valid instrument for rapid estimation of adherence to the Mediterranean diet and may be useful in clinical practice.

An alternative method for dating unknown tephras based on a segmented regression model

In CoDaWork’05, we presented an application of discriminant function analysis (DFA) to 4 differentcompositional datasets and modelled the first canonical variable using a segmented regression modelsolely based on an observation about the scatter plots. In this paper, multiple linear regressions areapplied to different datasets to confirm the validity of our proposed model. In addition to dating theunknown tephras by calibration as discussed previously, another method of mapping the unknown tephrasinto samples of the reference set or missing samples in between consecutive reference samples isproposed. The application of these methodologies is demonstrated with both simulated and real datasets.This new proposed methodology provides an alternative, more acceptable approach for geologists as theirfocus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age ofunknown tephra.Kew words: Tephrochronology; Segmented regression

Effect of biological surlie ageing on the sparkling wines’ quality and elaoration

Report for the scientific sojourn at the Université de Bourgogne, France, from July until October 2007..Surlie ageing after second fermentation is a fundamental operation in the production of quality sparkling wine like Cava and Champagne. Recently, the importance of the interaction between wine and lees cell surface has been reported. Cell surface properties depending on wall biochemical composition are major determinants in microbial interactions, having important repercussions in several technological aspects. Sorption and flocculation are especially important in sparkling wine production, and are governed by distinct cell surface properties. The aim of the present research carried out during the four months of the stage was to know the implication of lees surface modifications occurring during surlie ageing in sparkling wine quality and elaboration. The relationship between physico-chemical properties such as hydrophobicity, charge and electron-donor characteristics, and the yeast surface sorption capacities, we determined these factors in a model system. Then, real industrial lees samples were investigated. The surface properties of sparkling wine lees from the same strain of Saccharomyces cerevisiae were characterized according to the time of surlie ageing, and their possible influence on lees sorption and flocculation capacity was evaluated. Surlie ageing after second fermentation is a fundamental operation in the production of quality sparkling wine like Cava and Champagne. Recently, the importance of the interaction between wine and lees cell surface has been reported. Cell surface properties depending on wall biochemical composition are major determinants in microbial interactions, having important repercussions in several technological aspects. Sorption and flocculation are especially important in sparkling wine production, and are governed by distinct cell surface properties. The aim of the present research carried out during the four months of the stage was to know the implication of lees surface modifications occurring during surlie ageing in sparkling wine quality and elaboration. The relationship between physico-chemical properties such as hydrophobicity, charge and electron-donor characteristics, and the yeast surface sorption capacities, we determined these factors in a model system. Then, real industrial lees samples were investigated. The surface properties of sparkling wine lees from the same strain of Saccharomyces cerevisiae were characterized according to the time of surlie ageing, and their possible influence on lees sorption and flocculation capacity was evaluated.

Finite sample nonparametric tests for linear regressions

We introduce several exact nonparametric tests for finite sample multivariatelinear regressions, and compare their powers. This fills an important gap inthe literature where the only known nonparametric tests are either asymptotic,or assume one covariate only.

Constant coefficient tests for random coefficient regression

Random coefficient regression models have been applied in differentfields and they constitute a unifying setup for many statisticalproblems. The nonparametric study of this model started with Beranand Hall (1992) and it has become a fruitful framework. In thispaper we propose and study statistics for testing a basic hypothesisconcerning this model: the constancy of coefficients. The asymptoticbehavior of the statistics is investigated and bootstrapapproximations are used in order to determine the critical values ofthe test statistics. A simulation study illustrates the performanceof the proposals.

Exact tests for correlation and for the slope in simple linear regressions without making assumptions

We present an exact test for whether two random variables that have known bounds on their support are negatively correlated. The alternative hypothesis is that they are not negatively correlated. No assumptions are made on the underlying distributions. We show by example that the Spearman rank correlation test as the competing exact test of correlation in nonparametric settings rests on an additional assumption on the data generating process without which it is not valid as a test for correlation.We then show how to test for the significance of the slope in a linear regression analysis that invovles a single independent variable and where outcomes of the dependent variable belong to a known bounded set.

Herramientas estadísticas para el estudio de perfiles de riesgo

En este documento se ilustra de un modo práctico, el empleo de tres instrumentos que permiten al actuario definir grupos arancelarios y estimar premios de riesgo en el proceso que tasa la clase para el seguro de no vida. El primero es el análisis de segmentación (CHAID y XAID) usado en primer lugar en 1997 por UNESPA en su cartera común de coches. El segundo es un proceso de selección gradual con el modelo de regresión a base de distancia. Y el tercero es un proceso con el modelo conocido y generalizado de regresión linear, que representa la técnica más moderna en la bibliografía actuarial. De estos últimos, si combinamos funciones de eslabón diferentes y distribuciones de error, podemos obtener el aditivo clásico y modelos multiplicativos

Herramientas estadísticas para el estudio de perfiles de riesgo

En este documento se ilustra de un modo práctico, el empleo de tres instrumentos que permiten al actuario definir grupos arancelarios y estimar premios de riesgo en el proceso que tasa la clase para el seguro de no vida. El primero es el análisis de segmentación (CHAID y XAID) usado en primer lugar en 1997 por UNESPA en su cartera común de coches. El segundo es un proceso de selección gradual con el modelo de regresión a base de distancia. Y el tercero es un proceso con el modelo conocido y generalizado de regresión linear, que representa la técnica más moderna en la bibliografía actuarial. De estos últimos, si combinamos funciones de eslabón diferentes y distribuciones de error, podemos obtener el aditivo clásico y modelos multiplicativos

Adapting football to the child: an application of the logistic regression model in observational mewthodology.

Logistic regression is included into the analysis techniques which are valid for observationalmethodology. However, its presence at the heart of thismethodology, and more specifically in physical activity and sports studies, is scarce. With a view to highlighting the possibilities this technique offers within the scope of observational methodology applied to physical activity and sports, an application of the logistic regression model is presented. The model is applied in the context of an observational design which aims to determine, from the analysis of use of the playing area, which football discipline (7 a side football, 9 a side football or 11 a side football) is best adapted to the child"s possibilities. A multiple logistic regression model can provide an effective prognosis regarding the probability of a move being successful (reaching the opposing goal area) depending on the sector in which the move commenced and the football discipline which is being played.