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This paper suggests a new methodology capable of accessing in detail the contribution of companies to countries’ sustainability related to economic performance. The concept of sustainability has been brought up in several debates, leading to a clearer understanding of its progress in recent decades. The most adequate indicators to achieve a unique value to define sustainability have been identified. However, specific behaviors of economic agents such as exist in particularly large organizations, have rarely been exposed and evaluated regarding their positive or negative contribution to the increase of sustainability throughout the world. This paper proposes an integrated approach incorporating an evaluation of the positive and negative contributions to sustainability by means of a logistic biplot application. This allows the creation of a summarized index that combines all single sustainability indicators. These synthetic indices allow the positioning of each of the companies in a geometric representation for an original exploration of the sustainability paradigm. The supplied method permits accessing and evaluating information concerning specific behaviors of economic agents such as big companies. In our paper, we have followed the engagements towards sustainability of big corporations, individually or as groups, across the different activity sectors in Portugal and Spain.

IntroductionFeeding local forages to ruminants is a promising strategy for enhancing metabolic processes, promoting sustainable farming, and improving product quality. However, studies comparing the effects of different forages on rumen histology and meat attributes of heifers are limited and variable.Material and methodsThis study evaluated the benefits of incorporating local forages into heifer diets by comparing barley straw (BS) and oat hay (OH) on heifer attributes focusing on meat quality (MQ) and rumen status (RS). Sixteen crossbred (Charolais x Limousin) female heifers (7 months of age, 263 ± 10.50 kg) were randomly assigned to two dietary treatments (BS or OH) over 120 days.Results and discussionHeifers fed OH showed enhanced RS (p 0.05) were found in animal performance, chemical composition, and technological properties of the meat between the dietary groups, while lower levels (p

Ecuadorian cocoa possesses important organoleptic characteristics such as aroma and flavor, called fine and aromatic cocoa. The objective of this study was to evaluate the initial growth responses of young cocoa seedlings to glyphosate in a dose progression in 45 cocoa plants (5 months old), which were transplanted into pots with substrate adjusted to pH 6.0–6.5. Glyphosate doses (0 to 904 g e.e. ha−1) were applied every two weeks, evaluating the impact at 30 and 60 days post-application. Data on shikimate accumulation parameters, chlorophyll content and PSII quantum efficiency were subjected to multivariate analysis using a three-dimensional scatter plot. The results indicated that high concentrations of glyphosate contributed to higher shikimate concentration and lower PSII quantum efficiency. The findings for the variables crop damage, stem height and stem diameter were evaluated by ANOVA. Similarities were reported between the results of the variables height and diameter, and significant differences (p < 0.05) in the variable crop damage for all treatments were also reported. In terms of phytotoxic reaction and growth parameters, the most efficient treatment was DO4, since the seedlings with this dosage showed a low percentage of damage (10%) and the best indices in terms of height and diameter. The least efficient treatment was D15. The control plants (DO1) showed a crop damage of >50% because the absence of control favored weed proliferation. These indications highlight the need to adjust glyphosate doses according to the specific needs of each crop and the development stage of the plant in order to reduce negative effects and maximize potential benefits.

Water property parameters were analyzed over 9 months across six stations within the Estero Salado. The parameters under evaluation included nitrite (NO2−), nitrate (NO3−), phosphate (PO43−), ammonium (NH4+), temperature, pH, biochemical oxygen demand (BOD), conductivity, salinity, color, turbidity, suspended solids, hardness, and alkalinity. Additionally, the TRIX index (which measures chlorophyll, oxygen saturation, nitrogen, and phosphorus) was considered. The multivariate technique employed was partial triadic analysis (PTA), a specialized variant developed from STATIS, enabling the examination of the common structure’s stability across months and the positioning of stations and variables within a compromise space. This analysis elucidated a variability of 69% and 96%, respectively. Stations could be characterized based on their associations with specific variables, while the analysis also facilitated the identification of months impacting the common structure of pollution indicators.

Abstract The PHQ-9 questionnaire is a screening test worldwide used to measure depression. But it cannot be used in Costa Rica, due to the fact that it has not previously been validated for its population. The present study aims to show the validation of the PHQ-9 questionnaire and its variants (PHQ-2, PHQ-4, PHQ-8) in a population sample of adults residing in Costa Rica. A sample was collected (n = 1162) using a self-administered questionnaire. Confirmatory Factor Analysis (CFA), Receiver Operating Characteristic (ROC) curve, and Multiple Group Confirmatory Factor Analysis (MGCFA) were tested. One factor was found that explained 73.33% of the variance with excellent internal consistency (α = 0.928). Goodness-of-fit measures were adequate (RMSEA = 0.107; CFI = 0.948), as was diagnostic power at a cut-off of 10 (78.60 for Sensitivity and 27.95 for 1-Specificity). External validation indices were good (r = 0.843 with GAD-7, r = − 0.647 with RS14, and r = 0.301 with FCV19S), and the model showed invariance by sex (∆χ2 = 27.90; df = 27; p

Yield and stability are desirable characteristics that crops need to have high agronomic value; sugarcane stands out globally due to its diverse range of products and by-products. However, genotype-environment (G × E) interactions can affect the overall performance of a crop. The objective of this study is to identify genotypes with the highest yield and stability, as well as to understand their independent and interactive effects. A collection of 10 sugarcane varieties was evaluated, including Colombian, Dominican, Ecuadorian lines, and a group of clones planted across five different locations from 2018 to 2020. A two-way ANOVA along with the GGE biplot technique were used to analyze yield and stability. The ANOVA model shows highly significant effects in all cases (p < 0.001) except for the genotype by year and sector interaction (G × Y × S); however, the decomposition by sectors reveals a significant triple interaction in sector 04 (p < 0.05). The GGE biplot model accounted for up to 74.77% of the total variance explained in its PC1 and PC2 components. It also highlighted the group of clones as having the highest yield and environmental instability, and the Ecuadorian varieties EC-07 and EC-08 as having the best yield-stability relationship. We conclude that the combined results of the ANOVA and GGE biplot models provide a more synergistic and effective evaluation of sugarcane varieties, offering theoretical and practical bases for decision-making in the selection of specific varieties.

Livestock farming, especially the beef cattle sector, plays a crucial role in the economy and social and environmental balance and occupies a prominent position in Spain. The aim of this study is to highlight the positive impact of this sector in socioeconomic, food, natural heritage conservation, and environmental management aspects in order to obtain an accurate profile of the national panorama and to propose sample subgroups. For this purpose, 252 beef cattle farms in Spain were examined in detail, and the external logistic biplot (ELB) was used with a multivariate approach and from an algebraic and computational perspective. By addressing aspects such as infrastructure, feeding strategies, waste management, biodiversity, productivity, and sustainability, similarities and differences between cattle farms have been obtained, providing an analytical tool for the livestock sector and generating key knowledge on its functioning and contributions to society and the environment. The analysis revealed accuracy in the zootechnical classification of livestock farms, their feeding strategies, and genetics. Finally, significant regional differences in prevailing livestock practices were identified.

Vision-related quality of life (QoL) analyzes the visual function concerning individual well-being based on activity and social participation. Because QoL is a multivariate construct, a multivariate statistical method must be used to analyze this construct. In this paper, we present a methodology based on STATIS multivariate three-way methods to assess the real change in vision-related QoL for myopic patients by comparing their conditions before and after corneal surgery. We conduct a case study in Costa Rica to detect the outcomes of patients referred for myopia that underwent refractive surgery. We consider a descriptive, observational and prospective study. We utilize the NEI VFQ-25 instrument to measure the vision-related QoL in five different stages over three months. After applying this instrument/questionnaire, a statistically significant difference was detected between the perceived QoL levels. In addition, strong correlations were identified with highly similar structures ranging from 0.857 to 0.940. The application of the dual STATIS method found the non-existence of reconceptualization in myopic patients, but a statistically significant recalibration was identified. Furthermore, a real change was observed in all patients after surgery. This finding has not been stated previously due to the limitations of the existing statistical tools. We demonstrated that dual STATIS is a multivariate method capable of evaluating vision-related QoL data and detecting changes in recalibration and reconceptualization.

Abstract Background Response Shift (RS) refers to the idea that an individual may undergo changes in its health-related quality of life (HRQOL). If internal standard, values, or reconceptualization of HRQOL change over time, then answer to the same items by the same individuals may not be comparable over time. Traditional measures to evaluate RS is prone to bias and strong methodologies to study the existence of this phenomenon is required. The objective is to systematically identify, analyze, and synthesize the existing and recent evidence of statistical methods used for RS detection in HRQOL studies. Methods The analysis of selected studies between January 2010 and July 2020 was performed through a systematic review in MEDLINE/PubMed, Scopus, Web of Science, PsycINFO and Google Scholar databases. The search strategy used the terms “Health-Related Quality of Life” and “Response Shift” using the filters “Humans”, “Journal Article”, “English” and “2010/01/01–2020/07/31”. The search was made in August 2020. Results After considering the inclusion and exclusion criteria, from the total selected articles (675), 107 (15.9%) of the publications were included in the analysis. From these, 79 (71.0%) detected the existence of RS and 86 (80.4%) only used one detection method. The most used methods were Then Test (n = 41) and Oort’s Structural Equation Models (SEM) (n = 35). Other method used were Multiple Lineal Regression (n = 7), Mixed-Effect Regression (n = 6), Latent Trajectory Analysis (n = 6), Item Response Theory (n = 6), Logistics Regression (n = 5), Regression and Classification Trees (n = 4) and Relative Importance Method (n = 4). Most of these detected recalibration, including Then Test (n = 27), followed by Oort’s SEM that detected the higher combination of RS types: recalibration (n = 24), reprioritization (n = 13) and reconceptualization (n = 7). Conclusions There is a continuous interest of studying RS detection. Oort’s SEM becomes the most versatile method in its capability for detecting RS in all different types. Despite results from previous systematic reviews, same methods have been used during the last years. We observed the need to explore other alternative methods allowing same detection capacity with robust and highly precise methodology. The investigation on RS detection and types requires more study, therefore new opportunity grows to continue attending this phenomenon through a multidisciplinary perspective.

Lentinula edodes is known to show high nutritional and organoleptic properties and can be mixed with different by-products in the production of new foods with important functional characteristics. Cocoa pod husk (CPH) is the main by-product in the cocoa industry and presents important bioactivities. In this research, two mixtures were applied based on Lentinula edodes mushroom flour from fifty different strains (strain 1 to strain 50) and cocoa pod husk flour (CPHF): 60% Lentinula edodes mushroom flour from each strain mixed with 40% CPHF (Mixture 1), and 80% Lentinula edodes mushroom flour from each strain mixed with 20% CPHF (Mixture 2). The parameters evaluated were moisture, proteins, fat, total dietary fiber (TDF), ash, carbohydrates, antioxidant capacity, antimicrobial activity, pH and water activity (aw). The multivariate statistical techniques evaluated those samples that exhibited the highest degree of correlation with the distinct chemical and commercial parameters, showing that sample 13 of both mixture flours (M1 and M2) obtained by the mushrooms of L. edodes (strain 13) with CPH indicated the higher significant of the parameters. In addition, the sensory test of the best flour (sample 13) was applied to 50 panelists, presenting the best sensory characteristics, such as color, aroma, texture and general acceptability.

This paper aims to categorize countries by their e-participation index, according to political, capacity, and governmental environment factors; examine how they are projected based on these factors; and analyze whether this projection corresponds to the current state of e-participation development. It is the first study to provide an overview of the e-participation level using multivariate analysis techniques for three-way data analysis, specifically, the X-STATIS methodology and cluster analysis. These techniques enable the simultaneous representation of countries, factors, conditions, trajectories, and groupings, taking into account national conditions in the evolution of e-participation from 2008 to 2016. The results show that when the conditions of each country interact with the level of e-participation development, and depending on the economic development, 7% of countries are lagging behind in e-participation evolution, given their institutional and political capacity. This delay is particularly relevant in countries that enjoy a higher level of socioeconomic status. Meanwhile, 38% are above the level they would correspond to.

El Ranking de Shanghai (ARWU) ha alcanzado tal prestigio que una buena posición en esta lista está asociada a calidad y reputación. El objetivo de esta investigación es analizar si las universidades clasificadas en ARWU muestran el mejor desempeño académico. Se han seleccionado las tasas de Rendimiento, Graduación y Abandono de los estudiantes de Grado de las universidades españolas. Se ha realizado un análisis multivariante a través del método HJ-Biplot, estudiando el comportamiento respecto a estas tasas de las universidades que aparecen en el ranking. Los resultados prueban que ocupar los primeros puestos en Shanghai no garantiza los mejores resultados en el desempeño académico. La calidad universitaria debe abordarse, por tanto, desde una perspectiva multidimensional, en función de la estrategia que cada institución se marque para dar respuesta a sus misiones.

The first female registration at Spanish university takes place in the year 1872 when María Elena Maseras Ribera accesses the Faculty of Medicine at the University of Barcelona. Since then, the number of female students has been increasing and their access to different disciplines has varied according to the social circumstances, always having as reference the domestic model. This research identifies the specialties of higher education that do not present an equitable gender distribution. For their development, they have selected Bachelor's students Spanish universities in the last three academic courses. Results reveal statistically significant gender differences at some areas of study. Women presence Spanish universities is greater in careers considered by society according to its role in the family. Conversely, technical degrees –closer to male stereotypes-, to reflect a minority female participation.

In this work, a statistical method for the segmentation of samples and/or populations is presented, which is based on a ternary tree structure. This approach overcomes known limitations of other segmentation methods such as CHAID, concerning the multivariate response and the non-symmetric relationship between explanatory and response variables. The multivariate response segmentation problem is handled through latent class models, while the factorial decomposition of the explanatory capability of variables is based on the Non-Symmetrical Correspondence Analysis. Stop criteria based on the CATANOVA index and impurity measures are proposed. A Simulated Annealing based post-pruning strategy is considered to avoid over-fitting relative to the training set and guarantee a better generalization capability for the method.

We present the constituent elements of the pedagogical design of MOOC «Statistics to researchers» from the University of Salamanca to the goal of detailing its pedagogical design and the results obtained. We start from four themes: (I) type of statistical learning, features and the propositional network for its representation; (II) capabilities of the virtual environment to enhance the transfer of knowledge; (III) materials as resources to learning; (IV) the analysis of the technological tools. A case study-based research methodology is adopted and used the questionnaire as an instrument. We present the results of implementation proving its success with a 30% completion rate.

Governance is a characteristic of political systems that indicates the degrees of cooperation and interaction between a state and non-state actors when it comes to decision making that will have an impact on society. The aim of our research focuses on analysing the behaviour of the Worldwide Governance Indicators (WGI) over the 2002–2019 period, since we are interested in learning whether such indicators varied or remained constant. Moreover, we will gain insight into the evolution of these indicators across countries in different geographical areas. The techniques we have chosen for this research are as follows: Partial Triadic Analysis, also known as X-STATIS, to highlight the stable structure of the evolution of the indicators and countries along the years by means of building an average year; Tucker3 to highlight deeper relationships among countries, indicators and years. A comparative analysis of these methods will allow us to check whether the WGI are stable over the years studied or whether they vary over time, providing information about the differences between the Worldwide Governance Indicators (WGI) in several countries or geographical areas.

Background and Objectives: Currently, one of the most discouraging aspects for many patients undergoing dental procedures is the administration of anaesthesia. Consequently, there is a constant search for new techniques to avoid the invasive and painful nature of the injection. A new motorised syringe system (Dentapen®) has recently been developed, standing out for its convenience and ease of use. Material and Methods: Randomised, controlled, single-blind, and single-centre study including 178 voluntary adult participants aged between 18 and 90 years. Individuals were randomly assigned using a randomised table. Patients were asked to rate the level of pain experienced during the injections, using a 10-point visual analogue scale (VAS). The following data were recorded: pain index, heart rate, blood pressure, and saturation, both before and after anaesthesia. Results: Of the total 178 participants, 87 participants (48.9%) were men and 91 (51.1%) were women. The first variable to be assessed was the pain experienced by patients when anaesthetised with a syringe, obtaining a mean value of 2.63 ± 1.86 on the VAS with the conventional syringe and 1.06 ± 1.28 with the Dentapen® syringe, showing statistically significant differences (p-value < 0.01). When stratifying, based on the procedure that was undertaken, differences were also significant for all treatments (p-value < 0.01) except for endodontics, where differences were likely to be significant (p-value = 0.02). Conclusions: In conclusion, from a clinical standpoint, the Dentapen® syringe is a valid alternative to traditional infiltration syringes, causing minimum pain with the injection.

The present work analyzed a review of methods for analyzing sequences of matrices or dichotomous data. A new method for a sequence of dichotomous matrices with a different number of rows is presented; the Dichotomous STATIS DUAL. Suppose we match the sequence of matrices by different years, with this method. In that case, we can graphically represent the relations among the different columns of all the matrices, and the relations between those columns and the different years, because everything can be represented in the same plots. As in all STATIS methods, three different plots can get: (i) the interstructure, with the relations among the years; (ii) the compromise, with the stable part of the relations between the columns; and (iii) the intrastructure (also known as trajectories), with the relations between columns and years, in other words, the evolution of the columns through the time. This new mathematical method can be used with all kinds of dichotomous data, thanks to the software we propose. In the present work, the software was applied to the assessment of learning styles.

In this study, a data set of mycelial and cultural characteristics of hybrid strains of Pleurotus ostreatus and Pleurotus djamor were analyzed using three data-mining techniques: the K-medoids clustering algorithm, PCA biplot and the association rules algorithm. The characteristics evaluated were as follows: maximum velocity; lag phase; biomass; and exopolysaccharides content in the cultivation of 50 hybrid strains of Pleurotus ostreatus and 50 hybrid strains of Pleurotus djamor. Different mixtures of culture media were used to supplement Ecuadorian agricultural products. Data of the parameters obtained in the experimental methods were grouped into four clusters, obtaining a presentation of the hybrid strains of Pleurotus with a higher relation to each characteristic measured. Data-mining tools showed the hybrid strains cultivated on solid-culture media (M1 = malt extract agar and rice flour) and liquid-culture media (L1 = maltose, yeast extract and rice flour) presented the highest mycelial and cultural characteristics. These results are good indicators to improve the industrial production of edible fungi by using rice flour in the cultivation, contributing to the mushroom market and circular economy.

In recent years, social responsibility has been revolutionizing sustainable development. After the development of new mathematical techniques, the improvement of computers’ processing capacity and the greater availability of possible explanatory variables, the analysis of these topics is moving towards the use of different machine learning techniques. However, within the field of machine learning, the use of Biplot techniques is little known for these analyses. For this reason, in this paper we explore the performance of two of the most popular techniques in multivariate statistics: External Logistic Biplot and the HJ-Biplot, to analyse the data structure in social responsibility studies. The results obtained from the sample of companies representing the Fortune Global 500 list indicate that the most frequently reported indicators are related to the social aspects are labour practices and decent work and society. On the contrary, the disclosure of indicators is less frequently related to human rights and product responsibility. Additionally, we have identified the countries and sectors with the highest CSR in social matters. We discovered that both machine learning algorithms are extremely competitive and practical to apply in CSR since they are simple to implement and work well with relatively big datasets.

Multi-set multivariate data analysis methods provide a way to analyze a series of tables together. In particular, the STATIS-dual method is applied in data tables where individuals can vary from one table to another, but the variables that are analyzed remain fixed. However, when you have a large number of variables or indicators, interpretation through traditional multiple-set methods is complex. For this reason, in this paper, a new methodology is proposed, which we have called Sparse STATIS-dual. This implements the elastic net penalty technique which seeks to retain the most important variables of the model and obtain more precise and interpretable results. As a complement to the new methodology and to materialize its application to data tables with fixed variables, a package is created in the R programming language, under the name Sparse STATIS-dual. Finally, an application to real data is presented and a comparison of results is made between the STATIS-dual and the Sparse STATIS-dual. The proposed method improves the informative capacity of the data and offers more easily interpretable solutions.

Data of the commercial parameters of Pleurotus ostreatus and Pleurotus djamor were analyzed using the data mining technique: K-means clustering algorithm. The parameters evaluated were: biological efficiency, crop yield ratio, productivity rate, nutritional composition, antioxidant and antimicrobial activities in the production of fruit bodies of 50 strains of Pleurotus ostreatus and 50 strains of Pleurotus djamor, cultivated on the most representative agricultural wastes from the province of Guayas: 80% sugarcane bagasse and 20% wheat straw (M1), and 60% wheat straw and 40% sugarcane bagasse (M2). The database of the parameters obtained in experimental procedures was grouped into three clusters, providing a visualization of the strains with a higher relation to each parameter (vector) measured.

Antecedentes/Objetivo: La inteligencia emocional es una variable que ha sido objeto de un incremento notable de investigación a lo largo de los últimos años. La inteligencia emocional ha mostrado numerosas relaciones con múltiples variables psicológicas, destacando su conexión con diversos trastornos físicos y psicológicos. El objetivo del presente estudio es analizar los efectos directos e indirectos que la inteligencia emocional ejerce sobre la manifestación de sintomatología somática y psicológica, así como sobre el desarrollo de trastornos como el síndrome de burnout en un grupo de profesionales cuya labor social resulta esencial. Método: Se aplicaron las escalas Trait Meta-Mood Scale-24, Maslach Burnout Inventory-22 y General Health Questionnaire-28 a un total de 881 sacerdotes católicos latinoamericanos (M edad=45,89; DT edad=11,58). Resultados: Mediante path analysis se muestra el efecto que la inteligencia emocional, especialmente la atención y claridad emocional, ejerce sobre las alteraciones somáticas y psicológicas. Conclusiones: Tanto los trastornos específicos como el bienestar general presentan una relación clara con la inteligencia emocional. Proporcionar programas formativos efectivos que desarrollen la inteligencia emocional podría reducir la aparición de trastornos físicos y emocionales. © 2017 Asociación Española de Psicología Conductual. Published by Elsevier España, S.L.U. This is an open access article under the CC BY−NC−ND license (http://creativecommons. org/licenses/by−nc−nd/4.0/).

The aim of this study was to show a novel and accurate digital measurement protocol by analyzing the area and volume for interproximal tooth enamel surface reduction. In total, 14 lower teeth from all dental sectors were embedded into an epoxy resin and distributed as the lower dental arch, keeping the contact points. The experimental model was submitted to an intraoral digital impression before and after interproximal tooth enamel surface reduction using air-rotor strips and then re-contouring and polishing the interproximal enamel surfaces. These steps helped obtain standard tessellation language (STL) digital files. Furthermore, each tooth in the preoperative and postoperative full-arch STL digital files was segmented individually and aligned to analyze the area and volume of the interproximal tooth enamel surface reduction using engineering morphometry software. Descriptive analysis of the area and volume of the interproximal tooth enamel surface reduction was performed using a Student t-test. Higher enamel reduction area (3.53 ± 3.08 mm2) and volume (0.32 ± 0.22 mm3) values were shown on the distal surface compared with the area (2.97 ± 3.05 mm2) and volume (0.22 ± 0.16 mm3) of the enamel reduction on the mesial surface measured using the morphometric measurement digital protocol. The morphometric measurement protocol is an accurate digital measurement protocol for analyzing the area and volume of interproximal enamel surface reduction.

A biplot is a graphical representation of two-mode multivariate data based on markers for rows and columns often provided in a two-dimensional space. These markers define parameters that help to interpret goodness of fit, quality of the representation and variability and relationships between variables. However, such parameters are estimated as point values by the biplot, thus no information on the accuracy of the corresponding estimators is obtained. We propose a graphical methodology, that may be considered as an inferential version of a biplot, based on bootstrap confidence intervals for the mentioned parameters. We implement our methodology in an \verb"R" package and validate it with simulated and real-world data.

La Teoría de Respuesta al Ítem (TRI) se constituye como una fundamentación probabilística para medir constructos latentes al entender que los ítems son las unidades básicas de medición dentro de un instrumento. Un reciente estudio sobre la evaluación del cambio en la Calidad de Vida de 218 pacientes miopes operados con cirugía de láser Excimer corneal, realizado en la ciudad de San José de Costa Rica, evidenció cómo los pacientes que se sometieron a este tipo de cirugía mejoraron significativamente su calidad de vida. Para la recolección de los datos se aplicó el instrumento NEI-VFQ-25 que consta de 25 ítems que miden la Calidad de Vida Relacionada con la Visión (CVRV), agrupados en 12 subescalas. El instrumento debe ser utilizado al menos dos veces en cada paciente y generalmente se utiliza 4 ó 5 veces a lo largo del tiempo para poder evaluar el verdadero cambio en la CVRV. Esto implica un tiempo largo de ejecución, por esta razón se plantea estudiar la capacidad informativa de cada ítem para conocer si es posible simplificar el instrumento sin pérdida de información. Se aplicó el análisis de la TRI utilizando el programa MULTILOG, que incluye las estimaciones de los parámetros utilizando el método de máxima verosimilitud y el modelo de respuestas graduadas, lo que permitió evidenciar la capacidad de información y el poder discriminante de cada ítem. El estudio ha puesto de manifiesto que es factible conseguir un instrumento más simple con la misma capacidad informativa.

The CHAID (Chi-Squared Automatic Interaction Detection) treebased segmentation technique has been found to be an effective approach for obtaining meaningful segments that are predictive of a K-category (nominal or ordinal) criterion variable. CHAID was designed to detect, in an automatic way, the nteraction between several categorical or ordinal predictors in explaining a categorical response, but, this may not be true when Simpson’s paradox is present. This is due to the fact that CHAID is a forward selection algorithm based on the marginal counts. In this paper we propose a backwards elimination algorithm that starts with the full set of predictors (or full tree) and eliminates predictors progressively. The elimination procedure is based on Conditional Independence contrasts using the concept of entropy. The proposed procedure is compared to CHAID.

After evaluating problems in conceptualisation of Quality of Life outcomes and establishing an operational definition of HRQoL, we focus the attention on the different dimensions of Response Shift and the theoretical Models to explaining it. We pay special attention to Schwartz and Sprangers Model. If Gamma change is present, the construct under assessment is not stable for the patient; so it has no sense to compare scores because if an individual changes conceptualization of QoL over the course of time, then answers to the same items by the same individual may not be as comparable over time as originally thought. So, it is crucial to capture Response Shift before Alpha change is evaluated. The analytical approaches to assess Response Shift are discussed, paying special attention to the statistical aspects. We found several shortcomings of Ahmavaara’s Method for comparing factorial structures and we have developed some alternatives to capture Beta and Gamma components of Response Shift. Keywords: Health Related Quality of Life (HRQoL), Response Shift, Beta change, Gamma change, Dual Statis method.

En este trabajo presentamos los resultados de un estudio realizado sobre las mujeres empleadas en el servicio doméstico, cuyo objetivo es conocer e identificar los perfiles socioeconómicos y laborales de las mujeres que se dedican a dicha actividad. En el análisis se han encontrado cuatro grupos bien diferenciados: uno formado por las mujeres empleadas de hogar regularizadas; otro constituido por mujeres inmigrantes y dos grupos más constituidos por mujeres de nacionalidad española, en situación laboral irregular diferenciados sobre todo en función de su estado civil.