Food allergy (FA) prevalence data in infants and preschool-age children are sparse, and proposed risk factors lack confirmation. In this study, 19 children's day care centers (DCC) from 2 main Portuguese cities were selected after stratification and cluster analysis. An ISAAC's (International Study of Asthma and Allergies in Childhood) derived health questionnaire was applied to a sample of chi...

Fanconi anemia (FA) is a genetically heterogeneous, inherited blood disorder characterized by bone marrow failure, congenital malformations, and a predisposition to leukemias. Because FA cells are hypersensitive to DNA cross-linking agents and have chromosomal instability, FA has been viewed as a disorder of DNA repair. However, the exact cellular defect in FA cells has not been identified. Seq...

The properties of hierarchical nonlinear factor analysis (HNFA) recently introduced by Valpola and others [3] are studied by reconstructing values. The variational Bayesian learning algorithm for HNFA has linear computational complexity and is able to infer the structure of the model in addition to estimating the parameters. To compare HNFA with other methods, we continued the experiments with ...

Statistic classifiers operate on features that generally include both, useful and useless information. These two types of information are difficult to separate in feature domain. Recently, a new paradigm based on Factor Analysis (FA) proposed a model decomposition into useful and useless components. This method has successfully been applied to speaker recognition tasks. In this paper, we study ...

PURPOSE Factor analysis (FA) has become part and parcel in metabolic syndrome (MBS) research. Both exploration- and confirmation-driven factor analyzes are rampant. However, factor analytic results on MBS differ widely. A situation that is at least in part attributable to misapplication of FA. Here, our purpose was (i) to review factor analytic efforts in the study of MBS with emphasis on misus...

This article compares two techniques: Data Envelopment Analysis (DEA) and Factor Analysis (FA) to aggregate multiple inputs and outputs in the evaluation of decision making units (DMU). Dِata envelopment analysis (DEA), a popular linear programming technique, is useful to rate comparatively operational efficiency of DMUs based on their deterministic or stochastic input–output data. Factor analys...

Latent variable modeling is a commonly used data analysis tool in social sciences and other applied fields. The most popular latent variable models are factor analysis (FA) and latent class analysis (LCA). FA assumes that there is one or more continuous latent variables – called factors – determining the responses on a set of observed variables, while LCA assumes that there is an underlying cat...

The goal of the paper was to depict the status of FA from the historical and contemporary aspects of trait psychology and kinesiology research along with the guidelines for the use of FA methods. Researchers in psychology and kinesiology apply factor analytical methods in research of abilities and traits with the purpose of developing hierarchical theories of personality organization. However, ...

OBJECTIVE To validate the usefulness of a diffusional anisotropic capillary array phantom and to investigate the effects of diffusion tensor imaging (DTI) parameter changes on diffusion fractional anisotropy (FA) and apparent diffusion coefficient (ADC) using the phantom. MATERIALS AND METHODS Diffusion tensor imaging of a capillary array phantom was performed with imaging parameter changes, ...

water quality assessment provides a scientific basis for water resources development and management. this case study proposes a factor analysis- hopfield neural network model (fhnn) based on factor analysis method and hopfield neural network method. the results showed that the factor analysis (fa) technique was introduced to identify important water quality parameters. results revealed that bio...