980 resultados para Measurement Error
Resumo:
Does financial development result in capital being reallocated more rapidly to industries where it is most productive? We argue that if this was the case, financially developed countries should see faster growth in industries with investment opportunities due to global demand and productivity shifts. Testing this cross-industry cross-country growth implication requires proxies for (latent) global industry investment opportunities. We show that tests relying only on data from specific (benchmark) countries may yield spurious evidence for or against the hypothesis. We therefore develop an alternative approach that combines benchmark-country proxies with a proxy that does not reflect opportunities specific to a country or level of financial development. Our empirical results yield clear support for the capital reallocation hypothesis.
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Kirton's Adaption-Innovation Inventory (KAI) is a widely-used measure of "cognitive style." Surprisingly, there is very little research investigating the discriminant and incremental validity of the KAI. In two studies (n = 213), we examined whether (a) we could predict KAI scores with the "big five" personality dimensions and (b) the KAI scores predicted leadership behavior when controlling for personality and ability. Correcting for measurement error, we found that KAI scores were predicted mostly by personality and gender (multiple R = 0.82). KAI scores did not predict variance in leadership while controlling for established predictors. Our findings add to recent literature that questions the uniqueness and utility of cognitive style or similar "style" constructs; researchers using such measures must control for the big five factors and correct for measurement error to avoid confounded interpretations.
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Using Monte Carlo simulations and reanalyzing the data of a validation study of the AEIM emotional intelligence test, we demonstrated that an atheoretical approach and the use of weak statistical procedures can result in biased validity estimates. These procedures included stepwise regression-and the general case of failing to include important theoretical controls-extreme scores analysis, and ignoring heteroscedasticity as well as measurement error. The authors of the AEIM test responded by offering more complete information about their analyses, allowing us to further examine the perils of ignoring theory and correct statistical procedures. In this paper we show with extended analyses that the AEIM test is invalid.
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The OLS estimator of the intergenerational earnings correlation is biased towards zero, while the instrumental variables estimator is biased upwards. The first of these results arises because of measurement error, while the latter rests on the presumption that the education of the parent family is an invalid instrument. We propose a panel data framework for quantifying the asymptotic biases of these estimators, as well as a mis-specification test for the IV estimator. [Author]
Resumo:
Social scientists often estimate models from correlational data, where the independent variable has not been exogenously manipulated; they also make implicit or explicit causal claims based on these models. When can these claims be made? We answer this question by first discussing design and estimation conditions under which model estimates can be interpreted, using the randomized experiment as the gold standard. We show how endogeneity--which includes omitted variables, omitted selection, simultaneity, common methods bias, and measurement error--renders estimates causally uninterpretable. Second, we present methods that allow researchers to test causal claims in situations where randomization is not possible or when causal interpretation is confounded, including fixed-effects panel, sample selection, instrumental variable, regression discontinuity, and difference-in-differences models. Third, we take stock of the methodological rigor with which causal claims are being made in a social sciences discipline by reviewing a representative sample of 110 articles on leadership published in the previous 10 years in top-tier journals. Our key finding is that researchers fail to address at least 66 % and up to 90 % of design and estimation conditions that make causal claims invalid. We conclude by offering 10 suggestions on how to improve non-experimental research.
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Moisture sensitivity of Hot Mix Asphalt (HMA) mixtures, generally called stripping, is a major form of distress in asphalt concrete pavement. It is characterized by the loss of adhesive bond between the asphalt binder and the aggregate (a failure of the bonding of the binder to the aggregate) or by a softening of the cohesive bonds within the asphalt binder (a failure within the binder itself), both of which are due to the action of loading under traffic in the presence of moisture. The evaluation of HMA moisture sensitivity has been divided into two categories: visual inspection test and mechanical test. However, most of them have been developed in pre-Superpave mix design. This research was undertaken to develop a protocol for evaluating the moisture sensitivity potential of HMA mixtures using the Nottingham Asphalt Tester (NAT). The mechanisms of HMA moisture sensitivity were reviewed and the test protocols using the NAT were developed. Different types of blends as moisture-sensitive groups and non-moisture-sensitive groups were used to evaluate the potential of the proposed test. The test results were analyzed with three parameters based on performance character: the retained flow number depending on critical permanent deformation failure (RFNP), the retained flow number depending on cohesion failure (RFNC), and energy ratio (ER). Analysis based on energy ratio of elastic strain (EREE ) at flow number of cohesion failure (FNC) has higher potential to evaluate the HMA moisture sensitivity than other parameters. If the measurement error in data-acquisition process is removed, analyses based on RFNP and RFNC would also have high potential to evaluate the HMA moisture sensitivity. The vacuum pressure saturation used in AASHTO T 283 and proposed test has a risk to damage specimen before the load applying.
Resumo:
Current measures of ability emotional intelligence (EI)--including the well-known Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT)--suffer from several limitations, including low discriminant validity and questionable construct and incremental validity. We show that the MSCEIT is largely predicted by personality dimensions, general intelligence, and demographics having multiple R's with the MSCEIT branches up to .66; for the general EI factor this relation was even stronger (Multiple R = .76). As concerns the factor structure of the MSCEIT, we found support for four first-order factors, which had differential relations with personality, but no support for a higher-order global EI factor. We discuss implications for employing the MSCEIT, including (a) using the single branches scores rather than the total score, (b) always controlling for personality and general intelligence to ensure unbiased parameter estimates in the EI factors, and (c) correcting for measurement error. Failure to account for these methodological aspects may severely compromise predictive validity testing. We also discuss avenues for the improvement of ability-based tests.
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The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics (Rönkkö & Evermann, 2013) and proponents (Henseler et al., 2014) of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (1) can be truly characterized as a technique for structural equation modeling (SEM); (2) is able to correct for measurement error; (3) can be used to validate measurement models; (4) accommodates small sample sizes; (5) is able to provide null hypothesis tests for path coefficients; and (6) can be employed in an exploratory, model-building fashion. We summarize and elaborate further on the key arguments underlying the exchange, drawing from the broader methodological and statistical literature in order to offer additional thoughts concerning the utility of PLS-PM and ways in which the technique might be improved. We conclude with recommendations as to whether and how PLS-PM serves as a viable contender to SEM approaches for estimating and evaluating theoretical models.
Resumo:
Electric motors driven by adjustable-frequency converters may produce periodic excitation forces that can cause torque and speed ripple. Interaction with the driven mechanical system may cause undesirable vibrations that affect the system performance and lifetime. Direct drives in sensitive applications, such as elevators or paper machines, emphasize the importance of smooth torque production. This thesis analyses the non-idealities of frequencyconverters that produce speed and torque ripple in electric drives. The origin of low order harmonics in speed and torque is examined. It is shown how different current measurement error types affect the torque. As the application environment, direct torque control (DTC) method is applied to permanent magnet synchronous machines (PMSM). A simulation model to analyse the effect of the frequency converter non-idealities on the performance of the electric drives is created. Themodel enables to identify potential problems causing torque vibrations and possibly damaging oscillations in electrically driven machine systems. The model is capable of coupling with separate simulation software of complex mechanical loads. Furthermore, the simulation model of the frequency converter's control algorithm can be applied to control a real frequency converter. A commercial frequencyconverter with standard software, a permanent magnet axial flux synchronous motor and a DC motor as the load are used to detect the effect of current measurement errors on load torque. A method to reduce the speed and torque ripple by compensating the current measurement errors is introduced. The method is based on analysing the amplitude of a selected harmonic component of speed as a function oftime and selecting a suitable compensation alternative for the current error. The speed can be either measured or estimated, so the compensation method is applicable also for speed sensorless drives. The proposed compensation method is tested with a laboratory drive, which consists of commercial frequency converter hardware with self-made software and a prototype PMSM. The speed and torque rippleof the test drive are reduced by applying the compensation method. In addition to the direct torque controlled PMSM drives, the compensation method can also beapplied to other motor types and control methods.
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In mathematical modeling the estimation of the model parameters is one of the most common problems. The goal is to seek parameters that fit to the measurements as well as possible. There is always error in the measurements which implies uncertainty to the model estimates. In Bayesian statistics all the unknown quantities are presented as probability distributions. If there is knowledge about parameters beforehand, it can be formulated as a prior distribution. The Bays’ rule combines the prior and the measurements to posterior distribution. Mathematical models are typically nonlinear, to produce statistics for them requires efficient sampling algorithms. In this thesis both Metropolis-Hastings (MH), Adaptive Metropolis (AM) algorithms and Gibbs sampling are introduced. In the thesis different ways to present prior distributions are introduced. The main issue is in the measurement error estimation and how to obtain prior knowledge for variance or covariance. Variance and covariance sampling is combined with the algorithms above. The examples of the hyperprior models are applied to estimation of model parameters and error in an outlier case.
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In this thesis the X-ray tomography is discussed from the Bayesian statistical viewpoint. The unknown parameters are assumed random variables and as opposite to traditional methods the solution is obtained as a large sample of the distribution of all possible solutions. As an introduction to tomography an inversion formula for Radon transform is presented on a plane. The vastly used filtered backprojection algorithm is derived. The traditional regularization methods are presented sufficiently to ground the Bayesian approach. The measurements are foton counts at the detector pixels. Thus the assumption of a Poisson distributed measurement error is justified. Often the error is assumed Gaussian, altough the electronic noise caused by the measurement device can change the error structure. The assumption of Gaussian measurement error is discussed. In the thesis the use of different prior distributions in X-ray tomography is discussed. Especially in severely ill-posed problems the use of a suitable prior is the main part of the whole solution process. In the empirical part the presented prior distributions are tested using simulated measurements. The effect of different prior distributions produce are shown in the empirical part of the thesis. The use of prior is shown obligatory in case of severely ill-posed problem.
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We survey a number of papers that have focused on the construction of cross-country data sets on average years of schooling. We discuss the construction of the different series, compare their profiles and construct indicators of their information content. The discussion focuses on a sample of OECD countries but we also provide some results for a large non-OECD sample.
Resumo:
L’instrument le plus fréquemment utilisé pour la mesure de l’amplitude de mouvement du coude est le goniomètre universel. Or celui-ci ne fait pas l’unanimité : plusieurs auteurs remettent en question sa fiabilité et validité. Cette étude détaille donc, en trois étapes, une alternative beaucoup plus précise et exacte : une méthode radiographique de mesure. Une étude de modélisation a d’abord permis de repérer les sources d’erreur potentielles de cette méthode radiographique, à ce jour jamais utilisée pour le coude. La méthode a ensuite servi à évaluer la validité du goniomètre. À cette fin, 51 volontaires ont participé à une étude clinique où les deux méthodes ont été confrontées. Finalement, la mesure radiographique a permis de lever le voile sur l’influence que peuvent avoir différents facteurs démographiques sur l’amplitude de mouvement du coude. La méthode radiographique s’est montrée robuste et certaines sources d’erreurs facilement évitables ont été identifiées. En ce qui concerne l’étude clinique, l’erreur de mesure attribuable au goniomètre était de ±10,3° lors de la mesure du coude en extension et de ±7,0° en flexion. L’étude a également révélé une association entre l’amplitude de mouvement et différents facteurs, dont les plus importants sont l’âge, le sexe, l’IMC et la circonférence du bras et de l’avant-bras. En conclusion, l’erreur du goniomètre peut être tolérée en clinique, mais son utilisation est cependant déconseillée en recherche, où une erreur de mesure de l’ordre de 10° est inacceptable. La méthode radiographique, étant plus précise et exacte, représente alors une bien meilleure alternative.
Resumo:
Les modèles animaux d’arthrose permettent d’évaluer le potentiel d’agents thérapeutiques en phase préclinique de développement. Le présent ouvrage tient compte du chien comme modèle d’arthrose naturelle (chez l’animal de compagnie) ou expérimentale (par sectionnement chirurgical du ligament croisé crânial). Au sein des expérimentations, la force de réaction au sol verticale maximale, mesurée lors de l’analyse cinétique de la locomotion, est proposée comme témoin d’effets fonctionnels et structuraux sur ces modèles d’arthrose. Sur un modèle canin d’arthrose naturelle, le seuil de changement minimal détectable a été déterminé. Les changements au dysfonctionnement locomoteur peuvent désormais être cernés en s’affranchissant de la marge d’erreur inhérente à la mesure de la force verticale maximale. Il en découle l’identification de répondants lors d’essais cliniques entrepris chez le chien arthrosique. Une analyse rétrospective a, par la suite, déterminé un taux de répondants de 62.8% et d’une taille d’effet de 0.7 pour des approches thérapeutiques actuellement proposées aux chiens arthrosiques. Cette analyse détermina également que la démonstration d’une réponse thérapeutique était favorisée en présence d’un fort dysfonctionnement locomoteur. Sur un modèle canin d’arthrose par sectionnement chirurgical du ligament croisé crânial, la force verticale maximale a démontré une relation inverse avec certains types de lésions arthrosiques évaluées à l’aide d’imagerie par résonance magnétique. Également, la sensibilité de la force verticale maximale a été mise en évidence envers la détection d’effets structuraux, au niveau de l’os sous-chondral, par un agent anti-résorptif (le tiludronate) sur ce même modèle. Les expérimentations en contexte d’arthrose naturelle canine permettent de valider davantage les résultats d’essais cliniques contrôlés utilisant la force verticale maximale comme critère d’efficacité fonctionnelle. Des évidences cliniques probantes nécessaires à la pratique d’une médecine basée sur des faits sont ainsi escomptées. En contexte d’arthrose expérimentale, la pertinence d’enregistrer le dysfonctionnement locomoteur est soulignée, puisque ce dernier est en lien avec l’état des structures. En effectuant l’analyse de la démarche, de pair avec l’évaluation des structures, il est escompté de pouvoir établir la répercussion de bénéfices structurels sur l’inconfort articulaire. Cet ouvrage suggère qu’une plateforme d’investigations précliniques, qui combine le modèle canin d’arthrose par sectionnement chirurgical du ligament croisé crânial à un essai clinique chez le chien arthrosique, soit un moyen de cerner des bénéfices structuraux ayant des impacts fonctionnels. Le potentiel inférentiel de ces modèles canins d’arthrose vers l’Homme serait ainsi favorisé en utilisant la force verticale maximale.
Resumo:
Interaction effects are usually modeled by means of moderated regression analysis. Structural equation models with non-linear constraints make it possible to estimate interaction effects while correcting for measurement error. From the various specifications, Jöreskog and Yang's (1996, 1998), likely the most parsimonious, has been chosen and further simplified. Up to now, only direct effects have been specified, thus wasting much of the capability of the structural equation approach. This paper presents and discusses an extension of Jöreskog and Yang's specification that can handle direct, indirect and interaction effects simultaneously. The model is illustrated by a study of the effects of an interactive style of use of budgets on both company innovation and performance