Persona: Martínez Huertas, José Ángel
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Martínez Huertas
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José Ángel
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Publicación Quantum projections on conceptual subspaces: A deeper dive into methodological challenges and opportunities(SAGE, 2024) Martínez Mingo, Alejandro; Olmos, Ricardo; Jorge Botana, Guillermo; Martínez Huertas, José ÁngelIn alignment with the distributional hypothesis of language, the work “Quantum Projections on Conceptual Subspaces” (Martínez-Mingo A, Jorge-Botana G, Martinez-Huertas JÁ, et al. Quantum projections on conceptual subspaces. Cogn Syst Res 2023; 82: 101154) proposed a methodology for generating conceptual subspaces from textual information based on previous work (Martinez-Mingo A, Jorge-Botana G and Olmos R. Quantum approach for similarity evaluation in LSA vector space models. 2020). These subspaces enable the utilization of the quantum model of similarity put forth by Pothos and Busemeyer (Pothos E, Busemeyer J. A quantum probability explanation for violations of symmetry in similarity judgments. In Proceedings of the annual meeting of the cognitive science society, 2011, Vol. 33, No. 33), allowing for the empirical examination of the violations of assumptions concerning symmetry and triangular inequality (Tversky A. Features of similarity. Psychol Rev 1977; 84: 327–352; Yearsley JM, Barque-Duran A, Scerrati E, et al. The triangle inequality constraint in similarity judgments. Prog Biophys Mol Biol 2017; 130: 26–32), as well as the diagnosticity effect (Tversky A. Features of similarity. Psychol Rev 1977; 84: 327–352; Yearsley JM, Pothos EM, Barque-Duran A, et al. Context effects in similarity judgments. J Exp Psychol Gen 2022; 151: 711–717), within a data-driven environment. These psychological biases, deeply studied by authors such as Tversky and Kahneman, inform us about the limitations of modeling psychological similarity measures using tools from classical geometry. This commentary aims to offer methodological clarifications, discuss theoretical and practical implications, and speculate on future directions in this field of research. Concretely, it aims to propose the use of different contours (conceptual or contextual) to generate the subspaces, which lead to subspaces of terms or contexts. Once these contours are defined, a differentiation is proposed between Aggregated Terms Subspaces (ATSs), Aggregated Contexts Subspaces (ACSs), and Aggregated Features Subspaces (AFSs) depending on whether we define the subspaces by grouping the terms or contexts within the contour, or from the latent dimensions of the semantic space obtained in the contour window. Finally, new data is provided on the violation of the triangular inequality assumption through the application of the quantum similarity model to ATSs.Publicación Strong versus weak embodiment: Spatial iconicity in physical, abstract, and social semantic categories(Wiley, 2023-10) León, J. A.; Moreno, D.; Martín, L. A; Martínez Huertas, José ÁngelBackground Perceptual and action systems seem to be related to complex cognitive processes, but the scope of grounded or embodied cognition has been questioned. Zwaan and Yaxley (2003) proposed that cognitive processes of making semantic relatedness judgments can be facilitated when word pairs are presented in ways that their referents maintain their iconic configuration rather than their reverse-iconic configuration (the spatial iconicity effect). This effect has been observed in different semantic categories using specific experiments, but it is known that embodiment is highly dependent on task demands. Method The present study analyzed the spatial iconicity effect in three semantic categories (physical, abstract, and social) using the same experimental criteria to determine the scope of embodied cognition. In this reaction-time experiment, 75 participants judged the semantic relatedness of 384 word pairs whose experimental items were presented in their iconic or reverse-iconic configurations. Results Two mixed-effects models with crossed random effects revealed that the interaction between word meaning and spatial position was present only for physical concepts but neither for abstract nor social concepts. Conclusions Within the framework of strong and weak embodiment theories, the data support weak embodiment theory as the most explicative one.Publicación Estimate of planned and unplanned missing individual scores in longitudinal designs using continuous-time state-space models(American Psychological Association, 2024) Martínez Huertas, José Ángel; Estrada, Eduardo; Olmos, Ricardo; https://orcid.org/0000-0003-0899-4057; https://orcid.org/0000-0002-1298-6861Latent change score (LCS) models within a Continuous-Time State-Space Modeling framework (CT-SSM) provide a convenient statistical approach for analyzing developmental data. In this study, we evaluate the robustness of such an approach in the context of accelerated longitudinal designs (ALDs). ALDs are especially interesting because they imply a very high rate of planned data missingness. Additionally, most longitudinal studies present unexpected participant attrition leading to unplanned missing data. Therefore, in ALDs, both sources of data missingness are combined. Previous research has shown that ALDs for developmental research allow recovering the population generating process. However, it is unknown how participant attrition impacts the model estimates. We have three goals: (1) to evaluate the robustness of the group-level parameter estimates in scenarios with empirically plausible unplanned data missingness; (2) to evaluate the performance of Kalman scores (KS) imputations for individual data points that were expected but unobserved; and (3) to evaluate the performance of KS imputations for individual data points that were outside the age ranged observed for each case (i.e., to estimate the individual trajectories for the complete age range under study). In general, results showed lack of bias in the simulated conditions. The variability of the estimates increased with lower sample sizes and higher missingness severity. Similarly, we found very accurate estimates of individual scores for both planned and unplanned missing data points. These results are very important for applied practitioners in terms of forecasting and making individual-level decisions. R code is provided to facilitate its implementation by applied researchersPublicación Model Selection and Model Averaging for Mixed-Effects Models with Crossed Random Effects for Subjects and Items(['Taylor and Francis Group', 'Routledge'], 2021-02-26) Olmos, Ricardo; Ferrer, Emilio; Martínez Huertas, José Ángel::virtual::4270::600; Martínez Huertas, José Ángel; Martínez Huertas, José Ángel; Martínez Huertas, José ÁngelA good deal of experimental research is characterized by the presence of random effects on subjects and items. A standard modeling approach that includes such sources of variability is the mixed-effects models (MEMs) with crossed random effects. However, under-parameterizing or over-parameterizing the random structure of MEMs bias the estimations of the Standard Errors (SEs) of fixed effects. In this simulation study, we examined two different but complementary perspectives: model selection with likelihood-ratio tests, AIC, and BIC; and model averaging with Akaike weights. Results showed that true model selection was constant across the different strategies examined (including ML and REML estimators). However, sample size and variance of random slopes were found to explain true model selection and SE bias of fixed effects. No relevant differences in SE bias were found for model selection and model averaging. Sample size and variance of random slopes interacted with the estimator to explain SE bias. Only the within-subjects effect showed significant underestimation of SEs with smaller number of items and larger item random slopes. SE bias was higher for ML than REML, but the variability of SE bias was the opposite. Such variability can be translated into high rates of unacceptable bias in many replications.Publicación Quantifying the ideational context: political frames, meaning trajectories and punctuated equilibria in Spanish mainstream press during the Catalan nationalist challenge(['Taylor and Francis Group', 'Routledge'], 2023-12-13) Jorge Botana, Guillermo de; Olmos Albacete, Ricardo; Martínez Mingo, Alejandro; Olivas Osuna, José Javier; Martínez Huertas, José ÁngelThis article presents a quantitative method for mapping semantic spaces and tracing political frames’ trajectories, that facilitate the analysis of the connections between changes in ideas and socio-political phenomena. We test our approach in Spain, where the Catalan conflict fostered a competition in terms of decontestation of meanings of key political concepts. Using unsupervised machine learning, we track the salience, level of semantic fragmentation and fluctuations in meanings of 216 frames in the two largest Spanish newspapers, El País and El Mundo, throughout 8 years. This is achieved via the extraction, vectorization, and comparison of over 70,000 words. We apply Latent Semantic Analysis, an innovative methodology for the alignment of semantic spaces, and new institutional theory. Our exploratory study suggests that the evolution of many nationalism-related frames resembles a punctuated equilibrium model, and that political events in Catalonia, acted as critical junctures, altering the meanings reflected in the Spanish press.Publicación Recovering Crossed Random Effects in Mixed-Effects Models Using Model Averaging(PsychOpen, 2022-12-22) Olmos, Ricardo; Martínez Huertas, José ÁngelRandom effects contain crucial information to understand the variability of the processes under study in mixed-effects models with crossed random effects (MEMs-CR). Given that model selection makes all-or-nothing decisions regarding to the inclusion of model parameters, we evaluated if model averaging could deal with model uncertainty to recover random effects of MEMs-CR. Specifically, we analyzed the bias and the root mean squared error (RMSE) of the estimations of the variances of random effects using model averaging with Akaike weights and Bayesian model averaging with BIC posterior probabilities, comparing them with two alternative analytical strategies as benchmarks: AIC and BIC model selection, and fitting a full random structure. A simulation study was conducted manipulating sample sizes for subjects and items, and the variance of random effects. Results showed that model averaging, especially Akaike weights, can adequately recover random variances, given a minimum sample size in the modeled clusters. Thus, we endorse using model averaging to deal with model uncertainty in MEMs-CR. An empirical illustration is provided to ease the usability of model averaging.Publicación Can personality traits be measured analyzing written language? A meta-analytic study on computational methods(Elsevier, 2021) Moreno, José David; Olmos, Ricardo; Jorge Botana, Guillermo de; Botella, Juan; Martínez Huertas, José ÁngelIn the last two decades, empirical evidence has shown that personality traits could be related to the characteristics of written language. This study describes a meta-analysis that synthesizes 23 independent estimates of the correlations between the Big Five major personality traits, and some computationally obtained indicators from written language. The results show significant combined estimates of the correlations, albeit small to moderate according to Cohen’s conventions to interpret effect sizes, for the five traits (between r = 0.26 for agreeableness and neuroticism, and 0.30 for openness). These estimates are moderated by the type of information in the texts, the use of prediction mechanisms, and the source of publication of the primary studies. Generally, the same effective moderators operate for the five traits. It is concluded that written language analyzed through computational methods could be used to extract relevant information of personality. But further research is still needed to consider it as predictive or explanatory tool for individual differences.Publicación Enhancing topic-detection in computerized assessments of constructed responses with distributional models of language(Elsevier, 2021-12-15) Olmos, Ricardo; León, José A.; Martínez Huertas, José ÁngelUsually, computerized assessments of constructed responses use a predictive-centered approach instead of a validity-centered one. Here, we compared the convergent and discriminant validity of two computerized assessment methods designed to detect semantic topics in constructed responses: Inbuilt Rubric (IR) and Partial Contents Similarity (PCS). While both methods are distributional models of language and use the same Latent Semantic Analysis (LSA) prior knowledge, they produce different semantic representations. PCS evaluates constructed responses using non-meaningful semantic dimensions (this method is the standard LSA assessment of constructed responses), but IR endows original LSA semantic space coordinates with meaning. In the present study, 255 undergraduate and high school students were allocated one of three texts and were tasked to make a summary. A topic- detection task was conducted comparing IR and PCS methods. Evidence from convergent and discriminant validity was found in favor of the IR method for topic-detection in computerized constructed response assessments. In this line, the multicollinearity of PCS method was larger than the one of IR method, which means that the former is less capable of discriminating between related concepts or meanings. Moreover, the semantic representations of both methods were qualitatively different, that is, they evaluated different concepts or meanings. The implications of these automated assessment methods are also discussed. First, the meaningful coordinates of the Inbuilt Rubric method can accommodate expert rubrics for computerized assessments of constructed responses improving computer-assisted language learning. Second, they can provide high-quality computerized feedback accurately detecting topics in other educational constructed response assessments. Thus, it is concluded that: (1) IR method can represent different concepts and contents of a text, simultaneously mapping a considerable variability of contents in constructed responses; (2) IR method semantic representations have a qualitatively different meaning than the LSA ones and present a desirable multicollinearity that promotes the discriminant validity of the scores of distributional models of language; and (3) IR method can extend the performance and the applications of current LSA semantic representations by endowing the dimensions of the semantic space with semantic meanings.Publicación Adding maintaining factors to developmental models of anorexia nervosa: An empirical examination in adolescents(Beat (formerly Eating Disorders Association), 2021-02-23) Moreno Encinas, Alba; Graell Berna, Montserrat; Faya Barrios, María Mar; Treasure, Janet; Sepúlveda, Ana Rosa; Martínez Huertas, José ÁngelObjective A biopsychosocial approach has been proposed to explain the pathogenesis of anorexia nervosa (AN), despite only a few of the existing etiological models having received empirical support. The aim of this study was to empirically investigate Herpertz-Dahlmann, Seitz, and Konrad (2011, https://doi.org/10.1007/s00406-011-0246-y)’s developmental model and to consider if interpersonal reactions to the illness might serve as maintaining factors following the model proposed by Treasure and Schmidt (2013, https://doi.org/10.1186/2050-2974-1-13)Publicación Validation of the professional good care scale in nursing homes (GCS-NH)(BioMed Central, 2021-04-15) Pérez Rojo, Gema; López, Javier; Noriega, Cristina; Velasco, Cristina; Martínez Huertas, José ÁngelBackground: There is extensive concern about older people’s care in institutions, especially recently in the past years. One of the reasons is linked to the cases of elder abuse, not only shown by academic and scientific sources, but also by social and mass media and their impact on public perception of the institutional setting. What is more, current COVID-19 pandemic consequences on older people have provoked alarm and worry especially about what is happening in institutions. Methods: The sample for this study consists of 286 staff working in nursing homes in Spain. This study aimed to assess the psychometric properties of the Professional Good Care Scale in Nursing Homes (GCS-NH). Results: Results of parallel analyses and exploratory factor analyses (EFAs) showed a four-factor model for the 32- item scale: humanization (9 items), non-infantilization (10 items), respect (7 items) and empowerment (6 items). Then, psychometric properties were tested analysing internal consistency (reliability) and convergent, divergent and criterion validity. High internal consistency (reliability) and different validity evidence were obtained for the total scores of the GCS-NH and its subscales. GCS-NH scores were also capable of detecting risk of probable institutional elder abuse. Conclusions: Results show that this scale is an appropriate, valid, and reliable multidimensional instrument to evaluate good care in older institutionalized people by staff. Good care is an outcome of a complex construct in which a wide range of factors converge (staff, older people, and environmental characteristics). The GCS-NH has potential to be used as a multidimensional tool to assess good care.