The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

Least squares regression with errors in both variables: case studies

Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.

Adjust of regression models to estimate the rectal temperature of broilers for the first 14 days of life

The broiler rectal temperature (t rectal) is one of the most important physiological responses to classify the animal thermal comfort. Therefore, the aim of this study was to adjust regression models in order to predict the rectal temperature (t rectal) of broiler chickens under different thermal conditions based on age (A) and a meteorological variable (air temperature - t air) or a thermal comfort index (temperature and humidity index -THI or black globe humidity index - BGHI) or a physical quantity enthalpy (H). In addition, through the inversion of these models and the expected t rectal intervals for each age, the comfort limits of t air, THI, BGHI and H for the chicks in the heating phase were determined, aiding in the validation of the equations and the preliminary limits for H. The experimental data used to adjust the mathematical models were collected in two commercial poultry farms, with Cobb chicks, from 1 to 14 days of age. It was possible to predict the t rectal of conditions from the expected t rectal and determine the lower and superior comfort thresholds of broilers satisfactorily by applying the four models adjusted; as well as to invert the models for prediction of the environmental H for the chicks first 14 days of life.

Identification of clonally rearranged T-cell receptor beta chain genes in HTLV-I carriers as a potential instrument for early detection of neoplasia

We analyzed the genetic recombination pattern of the T-cell receptor beta-chain gene (TCR-beta) in order to identify clonal expansion of T-lymphocytes in 17 human T-lymphotropic virus type I (HTLV-I)-positive healthy carriers, 7 of them with abnormal features in the peripheral blood lymphocytes. Monoclonal or oligoclonal expansion of T-cells was detected in 5 of 7 HTLV-I-positive patients with abnormal lymphocytes and unconfirmed diagnosis by using PCR amplification of segments of TCR-beta gene, in a set of reactions that target 102 different variable (V) segments, covering all members of the 24 V families available in the gene bank, including the more recently identified segments of the Vbeta-5 and Vbeta-8 family and the two diversity beta segments. Southern blots, the gold standard method to detect T-lymphocyte clonality, were negative for all of these 7 patients, what highlights the low sensitivity of this method that requires a large amount of very high quality DNA. To evaluate the performance of PCR in the detection of clonality we also analyzed 18 leukemia patients, all of whom tested positive. Clonal expansion was not detected in any of the negative controls or healthy carriers without abnormal lymphocytes. In conclusion, PCR amplification of segments of rearranged TCR-beta is reliable and highly suitable for the detection of small populations of clonal T-cells in asymptomatic HTLV-I carriers who present abnormal peripheral blood lymphocytes providing an additional instrument for following up these patients with potentially higher risk of leukemia.

Measuring curriculum integration in the junior grades: the design of an instrument

This study \Alas initiated in response to the Junior Division Review (1985) publ ished by the Ministry of Education for the Province of Ontario. Curriculum integration is an element used within the educational paradigm designed by the Ontario Ministry of Education. It is a term frequent1y verbal ized b>' educators in this province, but because of 1 imi ted resource support regarding this methodology, it was open to broad interpretation resulting in an extreme v ar i at i on i nit simp 1 eme n tat i on • I n de ed, the Min i s try intimated that it was not occurring to any significant degree across the province. The objective of this thes is was· to define integration in the junior classroom and de-:.ign a meas.ur·ement in-:.tr-ument which would in turn high 1 i gh t indicators of curriculum integration. The :.tudy made a prel iminary, field-based survey of educa tiona 1 professionals in order to generate a relevant description of integrated curr-iculum programm i ng as def i ned in the j un i or classroom. The description was a compilation of views expressed by a random selection of teachers, consultants, supervisory officers and principals. The survey revea 1 ed a much more comprehens i ve vi et·<,l of the attributes of integrated programming than tradition would dictate and resulted in a functional definition tha t was broader than past prac t ices. Based on the information generated by this survey, an instrument ou t 1 in i ng program cr iter i a of was devised. an integrated junior cla~·sroom Th i s measuremen t i nstrumen t , designed for all levels of educators, was named uThe Han~.son I nstrumen t for the Measuremen t of Program Integrat ion in the Jun i or Cl assroom". It refl ected five categories intrinsic to the me thodol ogy of integration: Teacher Behaviour, Student Behaviour, Classroom Layout, Cl as~·r oom Environment and Progr amm i ng. Each category and the items therein were successfully tested in val idi ty and rel iabi 1 i ty checKs. Interestingly, the individual class was found to be the major variable programming in in the measuremen t the j un i or d i vis i on • of The integrated instrument demonstrated potential not onl)' a~· an initial measure of the degree of integrated curriculum, but as a guide to strategies to implement such a methodology.

Tests of Joint Hypotheses for Time Series Regression with a Unit Root

This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression \"F-Test\" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).

Développement d’un instrument d’évaluation des besoins de réadaptation des personnes atteintes de maladies respiratoires chroniques

La réadaptation pulmonaire est une intervention dont l’efficacité est largement reconnue. Cette efficacité a été établie grâce à l’utilisation d’instruments de mesure d’impact global. Les patients bénéficiant des programmes de réadaptation pulmonaire possèdent des caractéristiques variées et souffrent généralement de maladie pulmonaire obstructive chronique à différents degrés. En fonction de leurs différents besoins, les patients répondent de façon variable aux composantes d’un programme de réadaptation pulmonaire. Il est recommandé d’individualiser les programmes en fonction des besoins des patients afin d’en optimiser les effets. À cette fin, l’évaluation des besoins de réadaptation des patients est nécessaire. Comme il n’existe actuellement aucun instrument standardisé pour procéder à cette évaluation, nous avons entrepris d’en développer un à l’aide de méthodes qualitatives et quantitatives de recherche. Un modèle conceptuel d’évaluation des besoins de réadaptation des patients a été élaboré suite aux résultats tirés de groupes de discussion, de la consultation de dossiers médicaux et d’une recension des écrits. À partir de ce modèle, des items devant être sélectionnés de façon individualisée parmi cinq domaines (reconnaissance des besoins, connaissance, motivation, attentes et buts) ont été pré-testés. Les tendances générales concernant la validité des items contenus dans le prototype d’instrument ont été vérifiées lors d’une étude pilote auprès de 50 répondants en réadaptation. Les pistes d’investigation dégagées dans ce mémoire serviront aux études de validation plus approfondies dont devrait faire l’objet ce prototype d’instrument dans le futur.

Attitudes stigmatisantes envers les personnes vivant avec le VIH : développement et validation d’un instrument de mesure intégrant un dispositif participatif

Contexte : De manière générale, on considère que le processus de validation d’un instrument de mesure porte sur la validité et la fiabilité. Or, la nature dynamique et évolutive de certaines problématiques, comme la stigmatisation des personnes vivant avec le VIH (PVVIH), laisse croire qu’il est particulièrement important de réinvestir rapidement dans la pratique, les résultats produits par les mesures ainsi validées. Objectifs : La présente thèse vise à développer et valider une échelle de mesure des attitudes stigmatisantes envers les PVVIH en intégrant un dispositif participatif. La thèse utilise en partie les données d’une enquête de surveillance des attitudes envers les PVVIH au Québec, elle comporte trois études qui répondent aux trois objectifs spécifiques suivants : (1) valider la version révisée d’un instrument de mesure des attitudes favorables à la stigmatisation dans la population générale du Québec envers les PVVIH; (2) analyser la relation entre la mesure des attitudes favorables à la stigmatisation et le recours au dépistage du VIH dans la population générale du Québec; (3) décrire et analyser les processus de circulation et d’utilisation des connaissances produites par l’instrument de mesure dans les réseaux professionnels des membres d’un comité consultatif. Méthodes : Un comité consultatif réunissant plusieurs partenaires issus de différents milieux a été constitué dès l’obtention de la subvention. Il a été consulté et informé avant, pendant et après l’enquête téléphonique populationnelle (n=1500) ayant permis de colliger les données. L’Échelle des Attitudes Stigmatisantes envers les Personnes Vivant avec le VIH (EASE-PVVIH) a été validée au moyen de plusieurs analyses psychométriques : analyses factorielles exploratoires et confirmatives, corrélations, régression linéaire multiple, test-t, tests d’hypothèses d’invariance de la structure factorielle et alphas de Cronbach (objectif 1). L’association entre les attitudes favorables à la stigmatisation et le recours au dépistage du VIH a été testée à l’aide de régressions logistiques hiérarchiques (objectif 2). Quant aux processus de circulation et d’utilisation des connaissances dans les réseaux professionnels, ils ont été analysés au moyen d’une étude de cas rétrospective (objectif 3). Résultats : Les analyses ont révélé trois résultats importants. Premièrement, d’un point de vue psychométrique, l’EASE-PVVIH est un outil fiable et valide pour mesurer les attitudes stigmatisantes envers les personnes vivant avec le VIH. Deuxièmement, sous une certaine forme caractérisée par l’inquiétude éprouvée lors de rencontres occasionnelles, les attitudes stigmatisantes par rapport aux personnes vivant avec le VIH semblent nuire au recours au test de dépistage dans la population générale au Québec. Troisièmement, un dispositif participatif en particulier, soit un comité consultatif, semble être un moyen pour favoriser le réinvestissement rapide et étendre la portée des résultats produits par la recherche dans des actions concrètes de santé publique. Conclusion : Ces résultats mettent en lumière la portée d’un dispositif participatif pour la validation d’instrument de mesure. L’arrimage entre les préoccupations scientifiques et pratiques apparaît être une avenue prometteuse pour améliorer la qualité et la pertinence sociale des données produites par les mesures.

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 different compositional datasets and modelled the first canonical variable using a segmented regression model solely based on an observation about the scatter plots. In this paper, multiple linear regressions are applied to different datasets to confirm the validity of our proposed model. In addition to dating the unknown tephras by calibration as discussed previously, another method of mapping the unknown tephras into samples of the reference set or missing samples in between consecutive reference samples is proposed. 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 their focus is on mapping the unknown tephra with relevant eruptive events rather than estimating the age of unknown tephra. Kew words: Tephrochronology; Segmented regression

Construcció i validació d'un instrument per a l'avaluació d'aspectes rítmics en dansa.

Resumen tomado del autor. Contiene tabla de ejercicios de palmas y de zapateados, ficha de evaluación de ejercicios, tablas de resultados

A study of the effect of heat source location in a ventilated room using multiple regression analysis

Multiple regression analysis is a statistical technique which allows to predict a dependent variable from m ore than one independent variable and also to determine influential independent variables. Using experimental data, in this study the multiple regression analysis is applied to predict the room mean velocity and determine the most influencing parameters on the velocity. More than 120 experiments for four different heat source locations were carried out in a test chamber with a high level wall mounted air supply terminal at air change rates 3-6 ach. The influence of the environmental parameters such as supply air momentum, room heat load, Archimedes number and local temperature ratio, were examined by two methods: a simple regression analysis incorporated into scatter matrix plots and multiple stepwise regression analysis. It is concluded that, when a heat source is located along the jet centre line, the supply momentum mainly influences the room mean velocity regardless of the plume strength. However, when the heat source is located outside the jet region, the local temperature ratio (the inverse of the local heat removal effectiveness) is a major influencing parameter.

Power properties if invariant tests for spatial autocorrelation in linear regression

This paper derives some exact power properties of tests for spatial autocorrelation in the context of a linear regression model. In particular, we characterize the circumstances in which the power vanishes as the autocorrelation increases, thus extending the work of Krämer (2005). More generally, the analysis in the paper sheds new light on how the power of tests for spatial autocorrelation is affected by the matrix of regressors and by the spatial structure. We mainly focus on the problem of residual spatial autocorrelation, in which case it is appropriate to restrict attention to the class of invariant tests, but we also consider the case when the autocorrelation is due to the presence of a spatially lagged dependent variable among the regressors. A numerical study aimed at assessing the practical relevance of the theoretical results is included

The dependent variable problem in quantitative studies of Active Labour Market Programmes: uncovering hidden dynamics?

The question of what explains variation in expenditures on Active Labour Market Programs (ALMPs) has attracted significant scholarship in recent years. Significant insights have been gained with respect to the role of employers, unions and dual labour markets, openness, and partisanship. However, there remain significant disagreements with respects to key explanatory variables such the role of unions or the impact of partisanship. Qualitative studies have shown that there are both good conceptual reasons as well as historical evidence that different ALMPs are driven by different dynamics. There is little reason to believe that vastly different programs such as training and employment subsidies are driven by similar structural, interest group or indeed partisan dynamics. The question is therefore whether different ALMPs have the same correlation with different key explanatory variables identified in the literature? Using regression analysis, this paper shows that the explanatory variables identified by the literature have different relation to distinct ALMPs. This refinement adds significant analytical value and shows that disagreements are at least partly due to a dependent variable problem of ‘over-aggregation’.

A generalised Bayesian instrumental variable approach under student t-distributed errors with application

Bayesian analysis is given of an instrumental variable model that allows for heteroscedasticity in both the structural equation and the instrument equation. Specifically, the approach for dealing with heteroscedastic errors in Geweke (1993) is extended to the Bayesian instrumental variable estimator outlined in Rossi et al. (2005). Heteroscedasticity is treated by modelling the variance for each error using a hierarchical prior that is Gamma distributed. The computation is carried out by using a Markov chain Monte Carlo sampling algorithm with an augmented draw for the heteroscedastic case. An example using real data illustrates the approach and shows that ignoring heteroscedasticity in the instrument equation when it exists may lead to biased estimates.

Tests of sunspot number sequences: 3. Effects of regression procedures on the calibration of historic sunspot data

We use sunspot group observations from the Royal Greenwich Observatory (RGO) to investigate the effects of intercalibrating data from observers with different visual acuities. The tests are made by counting the number of groups RB above a variable cut-off threshold of observed total whole-spot area (uncorrected for foreshortening) to simulate what a lower acuity observer would have seen. The synthesised annual means of RB are then re-scaled to the full observed RGO group number RA using a variety of regression techniques. It is found that a very high correlation between RA and RB (rAB > 0.98) does not prevent large errors in the intercalibration (for example sunspot maximum values can be over 30 % too large even for such levels of rAB). In generating the backbone sunspot number (RBB), Svalgaard and Schatten (2015, this issue) force regression fits to pass through the scatter plot origin which generates unreliable fits (the residuals do not form a normal distribution) and causes sunspot cycle amplitudes to be exaggerated in the intercalibrated data. It is demonstrated that the use of Quantile-Quantile (“Q  Q”) plots to test for a normal distribution is a useful indicator of erroneous and misleading regression fits. Ordinary least squares linear fits, not forced to pass through the origin, are sometimes reliable (although the optimum method used is shown to be different when matching peak and average sunspot group numbers). However, other fits are only reliable if non-linear regression is used. From these results it is entirely possible that the inflation of solar cycle amplitudes in the backbone group sunspot number as one goes back in time, relative to related solar-terrestrial parameters, is entirely caused by the use of inappropriate and non-robust regression techniques to calibrate the sunspot data.