Bayesian estimation of a flexible bifactor generalized partial credit model to survey data

Item response theory (IRT) models provide an important contribution in the analysis of polytomous items, such as Likert scale items in survey data. We propose a bifactor generalized partial credit model (bifac-GPC model) with flexible link functions - probit, logit and complementary log-log - for use in analysis of ordered polytomous item scale data. In order to estimate the parameters of the proposed model, we use a Bayesian approach through the NUTS algorithm and show the advantages of implementing IRT models through the Stan language. We present an application to marketing scale data. Specifically, we apply the model to a dataset of non-users of a mobile banking service in order to highlight the advantages of this model. The results show important managerial implications resulting from consumer perceptions. We provide a discussion of the methodology for this type of data and extensions. Codes are available for practitioners and researchers to replicate the application.     

Things that make us different: analysis of deviance with time-use data

The constrained, non-normal nature of time-use data poses a challenge to ordinary analysis of variance. This paper investigates a computationally simple variance decomposition technique suitable for those data. As a by-product of the analysis, a measure of fit for systems of time-demand equations is proposed that possesses several useful properties.     

The contribution of the intervention in social networks and community social work at the local level to social and human development

ABSTRACT

The primary task of community social work is building social networks by reinforcing people's resources and those of the different environmental and social contexts from three dimensions: personal development, social development and organisational development. The new information technologies today establish a relationship of communication with local communities and citizens that promotes proximity to social networks. Social intervention is supported by a set of methods from human geography that can be used as tools to create maps of the territory and the networks for planning, diagnosing and classifying the management of community network intervention. In this discussion we set out to analyse the contribution of the intervention in social networks as a means of achieving a new configuration of social networks at the local level. This information is obtained from semi-structured interviews with social workers and other professionals in the social sphere in municipalities with over 100,000 inhabitants in the Madrid region (Spain). The research results show that intervention in social networks locally multiplies the opportunities to enhance the quality of people's social relationships, thus expanding their social support by strengthening their bonds, their personal network and support systems; secondly, it increases empowerment to facilitate a type of intervention to strengthen human potential and to gain autonomy and full citizenship.     

Goodness-of-fit tests for parametric regression with selection biased data

Consider the nonparametric location-scale regression model Y=m(X)+σ(X)ε$Y=m(X)+\sigma (X)\epsilon$, where the error ε$\epsilon$ is independent of the covariate X$X$, and m$m$ and σ$\sigma$ are smooth but unknown functions. The pair (X,Y)$(X,Y)$ is allowed to be subject to selection bias. We construct tests for the hypothesis that m(·)$m(·)$ belongs to some parametric family of regression functions. The proposed tests compare the nonparametric maximum likelihood estimator (NPMLE) based on the residuals obtained under the assumed parametric model, with the NPMLE based on the residuals obtained without using the parametric model assumption. The asymptotic distribution of the test statistics is obtained. A bootstrap procedure is proposed to approximate the critical values of the tests. Finally, the finite sample performance of the proposed tests is studied in a simulation study, and the developed tests are applied on environmental data.     

A dynamic general equilibrium analysis of the political economy of public education

The primary objective of this paper is to highlight the distinct roles of altruism and of self-interest in the political determination of a public education policy. I assess the relative importance of three factors in the determination of the equilibrium level of this policy: altruism, the impact of public funding of education on social security benefits, and its impact on factor prices. I then focus on the impact of implementing a social security system on the equilibrium levels of education funding and on welfare. I find that although in the benchmark economy, the presence of social security might generate support for public funding of education, its overall effect on the well-being of individuals is negative for any level of social security taxation.

Maternal knowledge,stimulation, and early childhood development in low‐income families in Colombia

Theoretical models assume that parental knowledge about child development and caregiving motivates parental stimulation, shaping child development. Evidence supporting these models is scarce in low‐ and middle‐income countries (LMICs). This study tests the relations between maternal knowledge, stimulation, and child development in a Colombian sample of 1,277 low‐income mothers and their children under the age of five. Mothers showed diverse knowledge about child development and caregiving. Moreover, maternal knowledge when children were 9–26 months old indirectly predicted growth in children's cognitive, receptive language, and gross motor skills at ages 27–46 months, partially through maternal engagement in stimulating activities with the child.     

Performance of asymmetric links and correction methods for imbalanced data in binary regression

In binary regression, imbalanced data result from the presence of values equal to zero (or one) in a proportion that is significantly greater than the corresponding real values of one (or zero). In this work, we evaluate two methods developed to deal with imbalanced data and compare them to the use of asymmetric links. The results based on simulation study show, that correction methods do not adequately correct bias in the estimation of regression coefficients and that the models with power links and reverse power considered produce better results for certain types of imbalanced data. Additionally, we present an application for imbalanced data, identifying the best model among the various ones proposed. The parameters are estimated using a Bayesian approach, considering the Hamiltonian Monte-Carlo method, utilizing the No-U-Turn Sampler algorithm and the comparisons of models were developed using different criteria for model comparison, predictive evaluation and quantile residuals.     

Discrete and continuous bivariate lifetime models in presence of cure rate: a comparative study under Bayesian approach

The modeling and analysis of lifetime data in which the main endpoints are the times when an event of interest occurs is of great interest in medical studies. In these studies, it is common that two or more lifetimes associated with the same unit such as the times to deterioration levels or the times to reaction to a treatment in pairs of organs like lungs, kidneys, eyes or ears. In medical applications, it is also possible that a cure rate is present and needed to be modeled with lifetime data with long-term survivors. This paper presented a comparative study under a Bayesian approach among some existing continuous and discrete bivariate distributions such as the bivariate exponential distributions and the bivariate geometric distributions in presence of cure rate, censored data and covariates. In presence of lifetimes related to cured patients, it is assumed standard mixture cure rate models in the data analysis. The posterior summaries of interest are obtained using Markov Chain Monte Carlo methods. To illustrate the proposed methodology two real medical data sets are considered.     

Needs assessment of youths in residential child care in Portugal / Evaluación de necesidades de jóvenes en acogimiento residencial en Portugal / Evaluación de necesidades de jóvenes en acogimiento residencial en Portugal

Residential child care in Portugal is the most common protection measure in cases of family separation, since family foster care is still very rare. However, little is known about the needs of these children and young people. The purpose of this study is to describe the profile of adolescents close to legal adulthood who are in residential care, comparing it with a Spanish sample. The sample is composed of 345 young people aged 16 to 17 on whom information has been collected regarding their history of protection, family background, schooling, mental health and offending behaviour. A Spanish sample was selected as a comparison group (N = 384). The results reveal the complexity and special seriousness of the profile of young people in residential care in Portugal compared to a Spanish sample, highlighting a high presence of mental health problems and especially suicidal behaviours. Given these results, efforts should be focused on developing specialized residential care programmes adapted to the specific needs of these young people.     

Rainfall interception by six urban trees in San Juan,Puerto Rico

Urban Ecosystems - Rainfall interception is an important part of the urban hydrological cycle. Understanding is limited about the role of urban trees and other vegetation in the interception...