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A Model for the Growth of Opportunistic Macroalgae (Enteromorpha sp.) in Tidal Estuaries

Martins, I.; Marques, J. C.
Fonte: Universidade de Coimbra Publicador: Universidade de Coimbra
Tipo: Artigo de Revista Científica Formato: aplication/PDF
ENG
Relevância na Pesquisa
55.87%
The aim of this work was to develop a model capable of simulating the gross and the net growth ofEnteromorpha sp. in tidal estuaries. The model was developed for the Mondego Estuary (Western Portugal) taking into account the key factors that control green macroalgae in the area. Enteromorpha gross growth was defined as a function of light, temperature, salinity and internal nutrients (N and P). Net growth was defined as gross growth minus respiration. The model was calibrated using a set of experimental data obtained in the laboratory under semi-controlled conditions. Sub-models of tidal height and light extinction coefficient variation were included for predicting macroalgal growth in the field, which constituted the model validation. According to the results, model predictions are well within the observed results, both in the laboratory and in the field. The largest discrepancies between predicted and observed values in the field refer to winter months and July. Possibly at these periods of the year, the prevailing external conditions (very low salinity in winter and high temperature and PFD in July) induced some physiological responses by Enteromorpha, which were not described by the model (e.g. sporulation, desiccation).; http://www.sciencedirect.com/science/article/B6WDV-46P41Y7-6/1/502b07a3e9a31e052428df8c50222c1c

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients

Aguiar, Fabio S.; Almeida, Luciana L.; Netto, Antonio Ruffino; Kritski, Afranio Lineu; Mello, Fernanda C. Q.; Werneck, Guilherme L.
Fonte: BIOMED CENTRAL LTD; LONDON Publicador: BIOMED CENTRAL LTD; LONDON
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
45.94%
Background: Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Methods: Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. Results: We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity...

Comparação de Métodos Diretos e de Dois-Passos na identificação de sistemas em malha fechada.; Comparison between direct and two-step methods in closed-loop system identification.

Alves, Vitor Alex Oliveira
Fonte: Biblioteca Digitais de Teses e Dissertações da USP Publicador: Biblioteca Digitais de Teses e Dissertações da USP
Tipo: Tese de Doutorado Formato: application/pdf
Publicado em 22/02/2011 PT
Relevância na Pesquisa
45.94%
A Identificação de Sistemas em Malha Fechada possui considerável apelo prático, uma vez que oferece maior segurança durante a coleta experimental de dados e ao mesmo tempo, em linhas gerais, proporciona a construção de modelos mais adequados para servir de base ao projeto de sistemas de controle. Esta Tese apresenta, como um de seus principais objetivos, a comparação dos Métodos Diretos aplicados à Identificação em Malha Fechada com a classe dos Métodos de Dois-Passos, que se enquadram na abordagem de Identificação Conjunta Entrada/Saída. Complementando esta comparação, propõe-se um novo algoritmo em Dois-Passos, a Dupla Filtragem. As propriedades de convergência deste método são analisadas em detalhe. O desempenho alcançado pelos modelos identificados pelos Métodos Diretos e com o uso dos Métodos de Dois-Passos aqui considerados a saber, Filtragem-u (VAN DEN HOF; SCHRAMA, 1993), Filtragem-y (HUANG; SHAH, 1997) e Dupla Filtragem são comparados em uma abordagem estatística por meio da aplicação de Simulações de Monte Carlo. Também se propõe uma variante ao método da Filtragem-u, proporcionando duas formas distintas de descrever a função de sensibilidade da saída associada ao processo sob estudo (FORSSELL; LJUNG...

Cotton irrigation scheduling in central Asia: model calibration and validation with consideration of groundwater contribution

Cholpankulov, E.D.; Inchenkova, O.P.; Paredes, P.; Pereira, L.S.
Fonte: John Wiley & sons Publicador: John Wiley & sons
Tipo: Artigo de Revista Científica
Publicado em //2008 ENG
Relevância na Pesquisa
56.04%
The calibration and validation of the irrigation scheduling simulation model ISAREG for Central Asian conditions were performed using cotton field observations in the Hunger Steppe over the period 1983–87, and in the Fergana Valley for 2001–03. The calibration referred to the crop coefficients and the soil water depletion factor for no stress. Groundwater contribution was considered in computations adopting a set of parametric equations used in ISAREG. Calibration and validation were performed by comparing the observed and simulated soil water content during each crop season. Various indicators of goodness of fit were used to assess model validation. For the Hunger Steppe, the validation also included the comparison of model-computed and field-measured crop evapotranspiration, which was performed with the energy balance method. Results obtained show a good agreement between field observations and model predictions, thus allowing use of the ISAREG model to generate and assess alternative irrigation schedules aimed at improved water use in Central Asia.

Basic validation procedures for regression models in QSAR and QSPR studies: theory and application

Kiralj,Rudolf; Ferreira,Márcia M. C.
Fonte: Sociedade Brasileira de Química Publicador: Sociedade Brasileira de Química
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/01/2009 EN
Relevância na Pesquisa
46.01%
Four quantitative structure-activity relationships (QSAR) and quantitative structure-property relationship (QSPR) data sets were selected from the literature and used to build regression models with 75, 56, 50 and 15 training samples. The models were validated by leave-one-out crossvalidation, leave-N-out crossvalidation (LNO), external validation, y-randomization and bootstrapping. Validations have shown that the size of the training sets is the crucial factor in determining model performance, which deteriorates as the data set becomes smaller. Models from very small data sets suffer from the impossibility of being thoroughly validated, failure and atypical behavior in certain validations (chance correlation, lack of robustness to resampling and LNO), regardless of their good performance in leave-one-out crossvalidation, fitting and even in external validation. A simple determination of the critical Nin LNO has been introduced by using the limit of 0.1 for oscillations in Q², quantified as the variation range in single LNO and two standard deviations in multiple LNO. It has been demonstrated that it is sufficient to perform 10 -25 y-randomization and bootstrap runs for a typical model validation. The bootstrap schemes based on hierarchical cluster analysis give more reliable and reasonable results than bootstraps relying only on randomization of the complete data set. Data quality in terms of statistical significance of descriptor -yrelationships is the second important factor for model performance.Variable selection that does not eliminate insignificant descriptor - yrelationships may lead to situations in which they are not detected during model validation...

A posteriori model validation for the temporal order of directed functional connectivity maps

Beltz, Adriene M.; Molenaar, Peter C. M.
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 27/08/2015 EN
Relevância na Pesquisa
45.98%
A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections...

Beyond Corroboration: Strengthening Model Validation by Looking for Unexpected Patterns

Chérel, Guillaume; Cottineau, Clémentine; Reuillon, Romain
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
Publicado em 14/09/2015 EN
Relevância na Pesquisa
45.94%
Models of emergent phenomena are designed to provide an explanation to global-scale phenomena from local-scale processes. Model validation is commonly done by verifying that the model is able to reproduce the patterns to be explained. We argue that robust validation must not only be based on corroboration, but also on attempting to falsify the model, i.e. making sure that the model behaves soundly for any reasonable input and parameter values. We propose an open-ended evolutionary method based on Novelty Search to look for the diverse patterns a model can produce. The Pattern Space Exploration method was tested on a model of collective motion and compared to three common a priori sampling experiment designs. The method successfully discovered all known qualitatively different kinds of collective motion, and performed much better than the a priori sampling methods. The method was then applied to a case study of city system dynamics to explore the model’s predicted values of city hierarchisation and population growth. This case study showed that the method can provide insights on potential predictive scenarios as well as falsifiers of the model when the simulated dynamics are highly unrealistic.

An application of conditional logistic regression and multifactor dimensionality reduction for detecting gene-gene Interactions on risk of myocardial infarction: The importance of model validation

Hebert, Patricia R; Ritchie, Marylyn D; Krumholz, Harlan M; Brown, Nancy J; Vaughan, Douglas E; Moore, Jason H; Coffey, Christopher S.; Gaziano, John Michael; Ridker, Paul M.
Fonte: BioMed Central Publicador: BioMed Central
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
45.98%
Background: To examine interactions among the angiotensin converting enzyme (ACE) insertion/deletion, plasminogen activator inhibitor-1 (PAI-1) 4G/5G, and tissue plasminogen activator (t-PA) insertion/deletion gene polymorphisms on risk of myocardial infarction using data from 343 matched case-control pairs from the Physicians Health Study. We examined the data using both conditional logistic regression and the multifactor dimensionality reduction (MDR) method. One advantage of the MDR method is that it provides an internal prediction error for validation. We summarize our use of this internal prediction error for model validation. Results: The overall results for the two methods were consistent, with both suggesting an interaction between the ACE I/D and PAI-1 4G/5G polymorphisms. However, using ten-fold cross validation, the 46% prediction error for the final MDR model was not significantly lower than that expected by chance. Conclusions: The significant interaction initially observed does not validate and may represent a type I error. As data-driven analytic methods continue to be developed and used to examine complex genetic interactions, it will become increasingly important to stress model validation in order to ensure that significant effects represent true relationships rather than chance findings.

Development of a large-scale golfer computer model to study swing kinematics

Tucker, Catherine; Kenny, Ian; Anderson, Ross
Fonte: Elsevier Publicador: Elsevier
Tipo: info:eu-repo/semantics/bookPart; all_ul_research
ENG
Relevância na Pesquisa
45.97%
peer-reviewed; Despite an increase in the number of full-body three-dimensional computer models of the golf swing reported in the literature, many authors do not report in detail how the models are validated. Therefore, the aim of this study was to create and validate a three-dimensional full-body computer model of a golfer with a driver in terms of its kinematic output. Single-subject analysis was used whereby one elite female golfer (handicap 0) performed 16 shots with her own driver club. A 6-camera Motion Analysis infrared camera system operating at 400 Hz recorded the kinematic data of the 27 markers located on the subject and golf club. Subsequently, this data was used to drive a computer model created in ADAMS/LifeMOD software. Model construction methods closely follow that of Nesbit (2005). Additional markers were placed on the subject and were used for model validation as opposed to driving the model. In order to initiate the movement of the model, inverse and forward dynamics calculations were carried out with the imported motion data captured from one representative trial captured during experimentation. The results illustrate a high level of correlation (average r=0.949) between the kinematic data collected in experimentation and the predicted trajectory of the virtual markers of the model. Furthermore...

Model validation and consistency

Gugercin, Serkan
Fonte: Universidade Rice Publicador: Universidade Rice
ENG
Relevância na Pesquisa
45.94%
This thesis addresses model validation, important in robust control system modeling, for the identification method developed by Antoulas. Given a system model, the problem is to assess whether the model is consistent with the data. This work formulates the validation problem in the form of a quadratic optimization problem subject to a spherical constraint. This new, computationally tractable method allows us to find a necessary and sufficient condition on the energy of the input sequence required to invalidate a given model. Therefore, for a given energy level, not all the models can be invalidated. For fixed noise level, the set of invalidatable models decreases as the energy of the input sequence decreases. Moreover, even if infinite length measurements are taken, the set of plants which cannot be invalidated does not shrink to the true model. The true model, in addition, can never be invalidated using an input of finite energy.

Solar Resource Mapping in the Maldives; Model Validation Report

World Bank Group
Fonte: World Bank, Washington, DC Publicador: World Bank, Washington, DC
Tipo: Report; Economic & Sector Work :: Energy Study; Economic & Sector Work
ENGLISH; EN_US
Relevância na Pesquisa
46.06%
This model validation report presents results of preliminary validation of solar resource and meteorological modelled data, within phase one of the project renewable energy resource mapping for the Republic of the Maldives. This part of the project focuses on solar resource mapping and measurement services as part of a technical assistance in the renewable energy development implemented by the World Bank in Maldives. It is being undertaken in close coordination with the ministry of environment and energy (MEE) of Maldives, the World Bank’s primary country counterpart for this project. The objective of this report is to document validation of solar resources calculated by satellite-based model SolarGIS and validation of meteorological data derived from the numerical weather model climate forecast system reanalysis (CFSR) and climate forecast system version two (CFSv2). Chapter one gives summary. Chapter two focuses on model quality indicators. Inventory in chapter three identifies the existing data sources in the region: solar...

The development of a naval battle model and its validation using historical data

Beall, Thomas Reagan.
Fonte: Monterey, California: Naval Postgraduate School Publicador: Monterey, California: Naval Postgraduate School
Tipo: Tese de Doutorado Formato: vii, 144 p.
EN_US
Relevância na Pesquisa
45.99%
Approved for public release; distribution is unlimited.; This thesis describes the development and validation of a naval battle model which incorporates a tactical theory by Captain Wayne P. Hughes, Jr. Opposing forces are portrayed as aggregations of the staying power and combat power of their individual platforms. Attrition is modeled as a force-on- force process and is expressed in terms of the degradation of each force's combat power and staying power throughout the engagement, user variation of model inputs concerning the timing, direction and strength of each force's fire permits analysis of the impact of scouting effectiveness and Command and Control on battle dynamics. Data from fourteen historical naval battles were gathered to compute model input parameters for the opposing forces and their interactions. The model's prediction of the outcome is compared with each battle's actual outcome. The conclusion drawn from this analysis that the model is a fair representation of reality. The model's potential for practical application is explored by using it to analyze the tactical options of the U.S. commander at the World War II Battle of Savo Island. Model results clearly indicate the weakness in U.S. tactics in this battle and suggest alternative tactics which afforded a better chance of success. (Author); Lieutenant...

Modeling growth and yield of loblolly pinestands under intensive management

Ferraz Filho,Antonio Carlos; Scolforo,José Roberto Soares; Oliveira,Antonio Donizette de; Mello,José Márcio de
Fonte: Embrapa Informação Tecnológica; Pesquisa Agropecuária Brasileira Publicador: Embrapa Informação Tecnológica; Pesquisa Agropecuária Brasileira
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/08/2015 EN
Relevância na Pesquisa
46%
Abstract:The objective of this work was to develop and validate a prognosis system for volume yield and basal area of intensively managed loblolly pine (Pinus taeda) stands, using stand and diameter class models compatible in basal area estimates. The data used in the study were obtained from plantations located in northern Uruguay. For model validation without data loss, a three-phase validation scheme was applied: first, the equations were fitted without the validation database; then, model validation was carried out; and, finally, the database was regrouped to recalibrate the parameter values. After the validation and final parameterization of the models, a simulation of the first commercial thinning was carried out. The developed prognosis system was precise and accurate in estimating basal area production per hectare or per diameter classes. There was compatibility in basal area estimates between diameter class and whole stand models, with a mean difference of -0.01 m2ha-1. The validation scheme applied is logic and consistent, since information on the accuracy and precision of the models is obtained without the loss of any information in the estimation of the models' parameters.

Model Validation in Ontology Based Transformations

Almendros-Jiménez, Jesús M.; Iribarne, Luis
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 22/10/2012
Relevância na Pesquisa
45.95%
Model Driven Engineering (MDE) is an emerging approach of software engineering. MDE emphasizes the construction of models from which the implementation should be derived by applying model transformations. The Ontology Definition Meta-model (ODM) has been proposed as a profile for UML models of the Web Ontology Language (OWL). In this context, transformations of UML models can be mapped into ODM/OWL transformations. On the other hand, model validation is a crucial task in model transformation. Meta-modeling permits to give a syntactic structure to source and target models. However, semantic requirements have to be imposed on source and target models. A given transformation will be sound when source and target models fulfill the syntactic and semantic requirements. In this paper, we present an approach for model validation in ODM based transformations. Adopting a logic programming based transformational approach we will show how it is possible to transform and validate models. Properties to be validated range from structural and semantic requirements of models (pre and post conditions) to properties of the transformation (invariants). The approach has been applied to a well-known example of model transformation: the Entity-Relationship (ER) to Relational Model (RM) transformation.; Comment: In Proceedings WWV 2012...

A General Strategy for Physics-Based Model Validation Illustrated with Earthquake Phenomenology, Atmospheric Radiative Transfer, and Computational Fluid Dynamics

Sornette, Didier; Davis, Anthony B.; Kamm, James R.; Ide, Kayo
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 01/10/2007
Relevância na Pesquisa
46.06%
Validation is often defined as the process of determining the degree to which a model is an accurate representation of the real world from the perspective of its intended uses. Validation is crucial as industries and governments depend increasingly on predictions by computer models to justify their decisions. In this article, we survey the model validation literature and propose to formulate validation as an iterative construction process that mimics the process occurring implicitly in the minds of scientists. We thus offer a formal representation of the progressive build-up of trust in the model, and thereby replace incapacitating claims on the impossibility of validating a given model by an adaptive process of constructive approximation. This approach is better adapted to the fuzzy, coarse-grained nature of validation. Our procedure factors in the degree of redundancy versus novelty of the experiments used for validation as well as the degree to which the model predicts the observations. We illustrate the new methodology first with the maturation of Quantum Mechanics as the arguably best established physics theory and then with several concrete examples drawn from some of our primary scientific interests: a cellular automaton model for earthquakes...

Computer model validation with functional output

Bayarri, M. J.; Berger, J. O.; Cafeo, J.; Garcia-Donato, G.; Liu, F.; Palomo, J.; Parthasarathy, R. J.; Paulo, R.; Sacks, J.; Walsh, D.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 21/11/2007
Relevância na Pesquisa
45.97%
A key question in evaluation of computer models is Does the computer model adequately represent reality? A six-step process for computer model validation is set out in Bayarri et al. [Technometrics 49 (2007) 138--154] (and briefly summarized below), based on comparison of computer model runs with field data of the process being modeled. The methodology is particularly suited to treating the major issues associated with the validation process: quantifying multiple sources of error and uncertainty in computer models; combining multiple sources of information; and being able to adapt to different, but related scenarios. Two complications that frequently arise in practice are the need to deal with highly irregular functional data and the need to acknowledge and incorporate uncertainty in the inputs. We develop methodology to deal with both complications. A key part of the approach utilizes a wavelet representation of the functional data, applies a hierarchical version of the scalar validation methodology to the wavelet coefficients, and transforms back, to ultimately compare computer model output with field output. The generality of the methodology is only limited by the capability of a combination of computational tools and the appropriateness of decompositions of the sort (wavelets) employed here. The methods and analyses we present are illustrated with a test bed dynamic stress analysis for a particular engineering system.; Comment: Published in at http://dx.doi.org/10.1214/009053607000000163 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

New Bayesian Updating Methodology for Model Validation and Robust Predictions Based on Data from Hierarchical Subsystem Tests

Cheung, Sai Hung; Beck, James
Fonte: Earthquake Engineering Research Laboratory Publicador: Earthquake Engineering Research Laboratory
Tipo: Report or Paper; PeerReviewed Formato: application/pdf
Publicado em 24/11/2008
Relevância na Pesquisa
46.02%
In many engineering applications, it is a formidable task to construct a mathematical model that is expected to produce accurate predictions of the behavior of a system of interest. During the construction of such predictive models, errors due to imperfect modeling and uncertainties due to incomplete information about the system and its input always exist and can be accounted for appropriately by using probability logic. Often one has to decide which proposed candidate models are acceptable for prediction of the target system behavior. In recent years, the problem of developing an effective model validation methodology has attracted attention in many different fields of engineering and applied science. Here, we consider the problem where a series of experiments are conducted that involve collecting data from successively more complex subsystems and these data are to be used to predict the response of a related more complex system. A novel methodology based on Bayesian updating of hierarchical stochastic system model classes using such experimental data is proposed for uncertainty quantification and propagation, model validation, and robust prediction of the response of the target system. After each test stage, we use all the available data to calculate the posterior probability of each stochastic system model along with the quality of its robust prediction. The proposed methodology is applied to the 2006 Sandia static-frame validation challenge problem to illustrate our approach for model validation and robust prediction of the system response. Recently-developed stochastic simulation methods are used to solve the computational problems involved.

Model Validation for Control and Controller Validation in a Prediction error Identification Framework - Part II: illustrations

Covers, Michel; Bombois, Xavier; Codrons, Bonoit; Scorletti, Gérard; Anderson, Brian
Fonte: Pergamon-Elsevier Ltd Publicador: Pergamon-Elsevier Ltd
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
65.99%
The results on model validation for control and controller validation in a prediction error identification framework are illustrated. The results are illustrated with two realistic identification and control design applications. The first is the control of a flexible mechanical system with a tracking objective and the second is the control of a ferrosilicon production process with a disturbance rejection objective.

Model Validation for Control and Controller Validation in a Prediction error Identification Framework - Part I

Gevers, Michel; Bombois, Xavier; Codrons, Bonoit; Scorletti, Gérard; Anderson, Brian
Fonte: Pergamon-Elsevier Ltd Publicador: Pergamon-Elsevier Ltd
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
66.06%
We propose a model validation procedure that consists of a prediction error identification experiment with a full order model. It delivers a parametric uncertainty ellipsoid and a corresponding set of parameterized transfer functions, which we call prediction error (PE) uncertainty set. Such uncertainty set differs from the classical uncertainty descriptions used in robust control analysis and design. We develop a robust control analysis theory for such uncertainty sets, which covers two distinct aspects: (1) Controller validation. We present necessary and sufficient conditions for a specific controller to stabilize - or to achieve a given level of performance with - all systems in such PE uncertainty set. (2) Model validation for robust control. We present a measure for the size of such PE uncertainty set that is directly connected to the size of a set controllers that stabilize all systems in the model uncertainty set. This allows us to establish that one uncertainty set is better tuned for robust control design than another, leading to control-oriented validation objectives.

Gestão por Competências na Administração Pública de Portugal: uma análise a partir do ciclo interligado de legitimação e de validação; Competence Management in Portugal Public Administration: an analysis from the interconnected cycle of legitimation and validation.

Munck, Luciano; Universidade Estadual de Londrina; Galleli, Bárbara; Universidade Estadual de Londrina; Borim-de-Souza, Rafael; Universidade Federal do Paraná
Fonte: Universidade Federal de Santa Catarina Publicador: Universidade Federal de Santa Catarina
Tipo: info:eu-repo/semantics/article; info:eu-repo/semantics/publishedVersion; ; Pesquisa teórica descritiva; Formato: application/pdf
Publicado em 09/04/2014 POR
Relevância na Pesquisa
45.98%
http://dx.doi.org/10.5007/2175-8077.2014v16n38p29O objetivo deste artigo é analisar o modelo de gestão de pessoas por competências da Administração Pública de Portugal a partir do Ciclo Interligado de Legitimação e de Validação Qualitativa. As categorias consideradas foram: definição constitutiva, validade de construto, composta pela validade de conteúdo, validade de face e confiabilidade e validade preditiva. A análise do modelo de gestão por competências de Portugal permitiu a identificação de pontos críticos em suas premissas, propostas e objetivos. Em suma, constatou-se que o modelo utilizado pela Administração Pública de Portugal tem comprovada a validade das definições constitutiva e operacional e a validade de face. Contudo, foram identificadas fragilidades na validade de construto, especificamente na validade de conteúdo, na confiabilidade e na validade preditiva. Portanto, conclui-se que erros podem circundar o modelo por completo. Em seu âmbito, o presente artigo identificou e discutiu questões centrais no que se refere à implantação e à validação de modelos de competências, pertinentes tanto para organizações públicas quanto privadas. ; The objective of this article is to analyze the model of people management by competences of Portugal Public Administration from the Interconnected Cycle of Legitimation and Qualitative Validation...