Search results for "Latent variable"
showing 10 items of 51 documents
Blind Source Separation Based on Joint Diagonalization in R: The Packages JADE and BSSasymp
2017
Blind source separation (BSS) is a well-known signal processing tool which is used to solve practical data analysis problems in various fields of science. In BSS, we assume that the observed data consists of linear mixtures of latent variables. The mixing system and the distributions of the latent variables are unknown. The aim is to find an estimate of an unmixing matrix which then transforms the observed data back to latent sources. In this paper we present the R packages JADE and BSSasymp. The package JADE offers several BSS methods which are based on joint diagonalization. Package BSSasymp contains functions for computing the asymptotic covariance matrices as well as their data-based es…
Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models
2021
In ecological community studies it is often of interest to study the effect of species related trait variables on abundances or presence-absences. Specifically, the interest may lay in the interactions between environmental and trait variables. An increasingly popular approach for studying such interactions is to use the so-called fourth-corner model, which explicitly posits a regression model where the mean response of each species is a function of interactions between covariate and trait predictors (among other terms). On the other hand, many of the fourth-corner models currently applied in the literature are too simplistic to properly account for variation in environmental and trait resp…
Blind source separation for non-stationary random fields
2022
Regional data analysis is concerned with the analysis and modeling of measurements that are spatially separated by specifically accounting for typical features of such data. Namely, measurements in close proximity tend to be more similar than the ones further separated. This might hold also true for cross-dependencies when multivariate spatial data is considered. Often, scientists are interested in linear transformations of such data which are easy to interpret and might be used as dimension reduction. Recently, for that purpose spatial blind source separation (SBSS) was introduced which assumes that the observed data are formed by a linear mixture of uncorrelated, weakly stationary random …
Testing equality of reliability and stability with simple linear constraints in multi-wave, multi-variable models
1998
Data from a longitudinal study on school achievement were used to develop new methods for analysing reliability of measurements and stability of behaviour over a long time interval. The proposed method of analysis makes it possible to test hypotheses about equality constraints on reliability and stability. It is known that the use of negative variances for imaginary latent variables with equality constraints between structural parameters produces standardized variances for endogenous latent variables and quality constraints for coefficients of stability. Reparameterization of random errors in measurement models allows equality constraints to be set for coefficients of cross-sectional and of…
Using System Dynamics to Model Student Performance in an Intelligent Tutoring System
2017
One basic adaptation function of an Intelligent Tutoring System (ITS) consists of selecting the most appropriate next task to be offered to the learner. This decision can be based on estimates, such as the expected performance of the student, or the probability that the student successfully solves each particular task. However, the computation of these values is intrinsically difficult, as they may depend on other complex latent variables that also need to be estimated from observable quantities, e.g. the current student's ability. In this work, we have used system dynamics to model learning and predict the student's performance in a given exercise, in an existing ITS that was developed to …
APROXIMACIÓN CONCEPTUAL Y PRÁCTICA A LOS MODELOS DE ECUACIONES ESTRUCTURALES
2017
En el presente trabajo se expone una aproximación conceptual y práctica a los Modelos de Ecuaciones Estructurales o Structural Equation Modeling (SEM). Los SEM están considerados entre las herramientas más potentes para el estudio de relaciones causales en datos no experimentales. Son una combinación del análisis factorial y la regresión múltiple y están compuestos por dos componentes: el modelo de medida y el modelo estructural. El modelo de medida describe la relación existente entre una serie de variables observables; mientras que en el modelo estructural se especifican las relaciones hipotetizadas entre las variables, es decir, se describen las relaciones entre las variables latentes me…
The Latent Factors Behind the Urban Travel Behaviour
2014
Abstract This research aims to explore the impact of latent variables, mirroring the users’ preferences, on the individual decision making process regarding the mode of transport. The paper describes the first results of an ongoing research activity, which derives from a pilot study carried out in Palermo. The authors have administered to a sample of travellers a questionnaire and they simulated the mode choice behaviour referring to the random utility theory. Then the transport demand over the entire area of Palermo has been studied in order to design the cordon pricing scenario with the application of an additional cost on private car dedicated to a selected area of the historic centre of…
Validation of the Cycling Behavior Questionnaire: A tool for measuring cyclists' road behaviors
2018
Abstract Introduction Even though cycling is an activity whose benefits in terms of urban mobility and health are globally recognized, its disproportional growth during the past few decades has led to some unexpected dynamics. In fact, the increasing number of traffic injuries and deaths involving cyclists has a high cost for public health systems. Considering the available empirical evidence, aberrant and positive behaviors on the road constitute relevant predictors for the injuries suffered by road users. Nevertheless, the scarcity of tools that measure and evaluate the behavior of road users, especially in the case of cyclists, constitutes a serious lack in terms of explaining, interveni…
Measuring the perceived value of rural tourism: a field survey in the western Sicilian agritourism sector
2016
Rural tourism constitutes a valuable tool for the sustainable development of many rural areas. This paper examines the concept of perceived value in rural tourism. A quantitative field survey was carried out in some main Western Sicilian holiday farms (agritourisms) during the Spring 2014. A theoretical model of the tourists’ perceived value in this specific context was developed and validated, using a 22-item scale. Using Partial Least Squares Path Modelling a theoretical structural model of the multidimensional structure of the RTPV was tested, assessing intensity and direction of the causal relationships among RTPV and its dimensions. Five dimensions were identified as forming the constr…
Bifactor analysis and construct validity of the five facet mindfulness questionnaire (FFMQ) in non-clinical Spanish samples
2015
The objective of the present study was to examine the dimensionality, reliability, and construct validity of the Five Facet Mindfulness Questionnaire (FFMQ) in three Spanish samples using structural equation modeling (SEM). Pooling the FFMQ data from 3 Spanish samples (n = 1191), we estimated the fit of two competing models (correlated five-factor vs. bifactor) via confirmatory factor analysis. The factorial invariance of the best fitting model across meditative practice was also addressed. The pattern of relationships between the FFMQ latent dimensions and anxiety, depression, and distress was analyzed using SEM. FFMQ reliability was examined by computing the omega and omega hierarchical c…