Statistical matching and uncertainty analysis in combining household income and expenditure data

Among the goals of statistical matching, a very important one is the estimation of the joint distribution of variables not jointly observed in a sample survey but separately available from independent sample surveys. The absence of joint information on the variables of interest leads to uncertainty about the data generating model since the available sample information is unable to discriminate among a set of plausible joint distributions. In the present paper a short review of the concept of uncertainty in statistical matching under logical constraints, as well as how to measure uncertainty for continuous variables is presented. The notion of matching error is related to an appropriate measure of uncertainty and a criterion of selecting matching variables by choosing the variables minimizing such an uncertainty measure is introduced. Finally, a method to choose a plausible joint distribution for the variables of interest via iterative proportional fitting algorithm is described. The proposed methodology is then applied to household income and expenditure data when extra sample information regarding the average propensity to consume is available. This leads to a reconstructed complete dataset where each record includes measures on income and expenditure.     

Project Re•Vision: disability at the edges of representation

The representational history of disabled people can largely be characterized as one of being put on display or hidden away. Self-representations have been a powerful part of the disability rights and culture movement, but recently scholars have analysed the ways in which these run the risk of creating a ‘single story’ that centres the experiences of white, western, physically disabled men. Here we introduce and theorize with Project Re?Vision, our arts-based research project that resists this singularity by creating and centring, without normalizing, representations that have previously been relegated to the margins. We draw from body becoming and new materialist theory to explore the dynamic ways in which positionality illuminates bodies of difference and open into a discussion about what is at stake when these stories are let loose into the world.     

Three Bartlett-type corrections for score statistics in symmetric nonlinear regression models

We present simple matrix formulae for corrected score statistics in symmetric nonlinear regression models. The corrected score statistics follow more closely a χ ² distribution than the classical score statistic. Our simulation results indicate that the corrected score tests display smaller size distortions than the original score test. We also compare the sizes and the powers of the corrected score tests with bootstrap-based score tests.     

A modified signed likelihood ratio test in elliptical structural models

In this paper we deal with the issue of performing accurate testing inference on a scalar parameter of interest in structural errors-in-variables models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as special case. We derive a modified signed likelihood ratio statistic that follows a standard normal distribution with a high degree of accuracy. Our Monte Carlo results show that the modified test is much less size distorted than its unmodified counterpart. An application is presented.     

A Two-Step Approach to Analyze Satisfaction Data

In this paper a two-step procedure based on Nonlinear Principal Component Analysis (NLPCA) and Multilevel models (MLM) for the analysis of satisfaction data is proposed. The basic hypothesis is that observed ordinal variables describe different aspects of a latent continuous variable, which depends on covariates connected with individual and contextual features. NLPCA is used to measure the level of a latent variable and MLM is adopted for detecting individual and environmental determinants of the level. This approach is suggested to analyze users’ satisfaction. In fact, NLPCA is used to create a synthetic continuous measure of satisfaction (first step) and MLM are used to detect the role of external (individual or environmental) variables that can affect the level itself (second step). The proposed two-step procedure is applied to the Eurobarometer survey data about opinion of European citizens on services of general interest (SGI) aiming to evaluate and compare the opinion about SGI in different countries. The focus is on overall level of satisfaction about four major public services: fixed telephone, electricity supply, postal and rail services. The item analyzed, which are named manifest variables, are: access easiness, price, quality, information clarity and contract fairness, as reported in the 2002 Eurobarometer survey. In the first step these variables are used to set up the synthetic indicator (the overall level) of satisfaction and, in the second step, a MLM is used to test the impact of some explanatory variables on this satisfaction.     

An improved class of estimators for the population mean

Starting from the Rao (Commun Stat Theory Methods 20:3325–3340, 1991) regression estimator, we propose a class of estimators for the unknown mean of a survey variable when auxiliary information is available. The bias and the mean square error of the estimators belonging to the class are obtained and the expressions for the optimum parameters minimizing the asymptotic mean square error are given in closed form. A simple condition allowing us to improve the classical regression estimator is worked out. Finally, in order to compare the performance of some estimators with the regression one, a simulation study is carried out when some population parameters are supposed to be unknown.     

Until work do us part: Labour migration and occupational stratification in non-cohabiting marriage

While recent decades have seen considerable research on cohabitation without marriage, the study of marriage without cohabitation has not fared as well. Prior work on the latter has emphasized the importance of occupational stratification, but ignored the social context around occupation, particularly regarding labour mobility and economic development. In this paper, we outline the significance of contemporary labour mobility and concomitant occupational stratification for the risk of non-cohabiting marriage, and use data from the IPUMS–International project to provide a cross-national accounting of non-cohabiting marriage. We focus on two issues: first, how does prevalence vary across countries, across time, and with respect to economic development? Second, how do the core dynamics of labour mobility—including migration, occupational status, and economic development—influence the probability of non-cohabiting marriage? Results indicate broad cross-national differences in prevalence, increasing risk over time, and a pattern of accumulating risk associated with multifaceted social disadvantage.     

Concepts travelling across disciplinary fields: the case of the business model

Journal of Management and Governance - Since the beginning of the 2000s, the concept of Business Model has been explored by scholars from a broad range of business studies and particularly those in...     

Analysis of the ergonomic usage of the ARMflex in the odontological area

The aim of this paper is to analyze the importance and applicability of ARMflex in the odontological area and its influence in preventing or stopping the involuntary habit of improperly positioning the hand under the face or under the pillow. The ergonomic usage of ARMflex influences the design in odontological areas and innovates in the semi-immobilization of the patient to prevent future orthodontic problems.