Imputación múltiple de valores perdidos en el análisis factorial exploratorio de escalas multidimensionales: estimación de las puntuaciones de rasgos latentes

Researchers frequently have to analyze scales in which some participants have failed to respond to some items. In this paper we focus on the exploratory factor analysis of multidimensional scales (i.e., scales that consist of a number of subscales) where each subscale is made up of a number of Likert-type items, and the aim of the analysis is to estimate participants’ scores on the corresponding latent traits. Our approach uses the following steps: (1) multiple imputation creates several copies of the data, in which the missing values are imputed; (2) each copy of the data is subject to independent factor analysis, and the same number of factors is extracted from all copies; (3) all factor solutions are simultaneously orthogonally (or obliquely) rotated so that they are both (a) factorially simple, and (b) as similar to one another as possible; (4) latent trait scores are estimated for ordinal data in each copy; and (5) participants’ scores on the latent traits are estimated as the average of the estimates of the latent traits obtained in the copies. We applied the approach in a real dataset where missing responses were artificially introduced following a real pattern of non-responses and a simulation study based on artificial datasets. The results show that our approach was able to compute factor score estimates even for participants that have missing data.Los investigadores con frecuencia se enfrentan a la difícil tarea de analizar las escalas en las que algunos de los participantes no han respondido a todos los ítems. En este artículo nos centramos en el análisis factorial exploratorio de escalas multidimensionales (es decir, escalas que constan de varias de subescalas), donde cada subescala se compone de una serie de ítems de tipo Likert, y el objetivo del análisis es estimar las puntuaciones de los participantes en los rasgos latentes correspondientes. En este contexto, se propone un nuevo enfoque para hacer frente a las respuestas faltantes que se basa en (1) la imputación múltiple de las respuestas faltantes y (2) la rotación simultánea de las muestras de datos imputados. Se ha aplicado el método en una muestra de datos reales en que las respuestas que faltantes fueron introducidas artificialmente siguiendo un patrón real de respuestas faltantes, y un estudio de simulación basado en conjuntos de datos artificiales. Los resultados muestran que nuestro enfoque (en concreto, Hot-Deck de imputación múltiple seguido de rotación Consensus Promin) es capaz de calcular correctamente la puntuación factorial estimada incluso para los participantes que tienen valores perdidos

MultipleCar: A Graphical User Interface MATLAB Toolbox to Compute Multiple Correspondence Analysis

In this paper we present the toolbox MultipleCar, which is a general program for computing multiple correspondence analysis and which was designed using a graphical user interface. The procedures implemented in MultipleCar are the usual ones that are already available in other applications, plus some additional procedures. MultipleCar makes it possible to compute (1) joint correspondence analysis, and (2) orthogonal and oblique rotation of coordinates. Although MultipleCar was developed in MATLAB, we compiled it as a standalone application for Windows operative systems based on graphical user interfaces. The users can decide whether to use the advanced MATLAB version of MultipleCar, or the standalone version (which does not require any programming skills)

CAR: A MATLAB Package to Compute Correspondence Analysis with Rotations

Correspondence analysis (CA) is a popular method that can be used to analyse relationships between categorical variables. Like principal component analysis, CA solutions can be rotated both orthogonally and obliquely to simple structure without affecting the total amount of explained inertia. We describe a MATLAB package for computing CA. The package includes orthogonal and oblique rotation of axes. It is designed not only for advanced users of MATLAB but also for beginners. Analysis can be done using a user-friendly interface, or by using command lines. We illustrate the use of CAR with one example.

Cómo afectan los sesgos de respuesta a la estructura factorial de los tests basados en el modelo de los Cinco Grandes factores de personalidad

Several studies have shown that personality self-reports may be affected by response biases, and that this may have consequences on their factor structure, especially in samples with little education or in adolescents. The current study aims to understand the effect of social desirability and acquiescence on the factor structure of three questionnaires based on the Five Factor Model of personality: the Big Five Inventory, the Five Factor Personality Inventory and the Overall Personality Assessment Scale. The data was analysed using a new method that removes the effects of both social desirability and acquiescence from the inter-item correlation matrix used for factor analysis. These effects were assessed in a sample of 392 university students, which contained no individuals with low educational levels, children or adolescents. The results showed that, even in samples with no individuals with low educational levels, controlling for social desirability and acquiescence led to a simpler factor structure that is more congruent with the theoretical solution expected from the five factor model. It also seems that in the domain of inventories based upon the five factor model, this effect may be specially due to acquiescence.sDiversos estudios muestran que los tests de personalidad pueden verse afectados por los sesgos de respuesta, lo que puede tener consecuencias en su estructura factorial, especialmente en muestras con bajo nivel educativo o adolescentes. El objetivo del presente estudio consiste en determinar cuál es el efecto de la deseabilidad social y la aquiescencia en la estructura factorial de tres cuestionarios basados en el modelo de los Cinco Grandes factores de personalidad: Big Five Inventory, Five Factor Personality Inventory y Overall Personality Assessment Scale. Los datos se analizaron a partir de un nuevo método que elimina los efectos de la deseabilidad social y la aquiescencia de la matriz de correlaciones inter-item utilizada en el análisis factorial. La muestra está compuesta por 392 estudiantes universitarios, por lo que no incluye individuos con bajo nivel educativo, niños o adolescentes. Los resultados indican que, incluso en muestras sin individuos con bajo nivel educativo, controlar la deseabilidad social y la aquiescencia da lugar a una estructura factorial más simple y congruente con la solución teórica esperada a partir del modelo de los Cinco Grandes. Además, los resultados sugieren que en los tests basados en este modelo, este efecto puede ser debido especialmente a la aquiescencia

Robust Promin: a method for diagonally weighted factor rotation

Oblique rotation of factors is usually performed in exploratory factor analysis in order to achieve the best and simplest interpretation of the solution based on the prescribed number of factors. Currently available algorithms, however, do not take into account the fluctuation of the correlations on which the factor solution is based. If such correlations’ stability is low, the rotated solution obtained in a specific sample may substantially differ from the rotated solutions obtained in different samples from the same population. The present paper proposes a modified version of the Promin rotation designed to achieve simple and stable rotated solutions through the samples. The usefulness of Robust Promin is illustrated by using an empirical example based on a real dataset. The procedure proposed in this paper has been implemented in the FACTOR factor analysis program version 10.9

Psychological Test Toolbox: A New Tool to Compute Factor Analysis Controlling Response Bias

The effects of response bias in psychological tests have been investigated for years, the two most common being social desirability (SD) and acquiescence (AC). However, the traditional methods for controlling or eliminating the impact of those biases in participants' scores have several limitations. Some factor analysis-based methods can overcome some of these limitations, such as the procedure proposed by Ferrando, Lorenzo-Seva, and Chico (2009). Nevertheless, this method involves programming skills that are not common among applied researchers or clinicians. Consequently, we have developed a stand-alone, user-friendly application that provides an easy way of using the aforementioned method to perform a factor analysis which controls for the effect of AC and SD. The program has been developed in the MATLAB environment and its distribution is entirely free

Incremental validity of Emotional Intelligence Perceived in predicting well-being

El objetivo del presente trabajo fue valorar la relación entre Inteligencia Emocional Percibida (IEP), medida por la Escala del Metaconocimiento del Estado de Ánimo (TMMS), el bienestar subjetivo (SWS) y el optimismo/pesimismo disposicional. Además, valoramos si la IEP se puede considerar un adecuado predictor del bienestar subjetivo (SWS). Los participantes fueron 518 adultos, 434 mujeres y 84 hombres. Todos ellos respondieron de forma anónima medidas de satisfacción en la vida, afecto positivo y negativo, inteligencia emocional percibida y optimismo/pesimismo disposicional. Hemos utilizado el método de Johnson para valorar los pesos relativos de cada una de las variables predictoras en una regresión múltiple. Nuestros resultados señalan que dos dimensiones de IEP (Claridad y Reparación) son buenos predictores de SWS, mientras la tercera dimensión, Atención emocional, parece no ser un adecuado predictorThe aim of the present study was to assess the relationship between Perceived Emotional Intelligence (PEI) as measured by the Trait Meta-Mood Scale (TMMS), Subjective Well-Being (SWB), and dispositional optimism/pessimism. In addition, we assessed whether PEI can be considered an adequate predictor of the SWB. Participants were 518 adults, 434 males and 84 females who anonymously completed measures of satisfaction with life, positive and negative affect, perceived emotional intelligence, and dispositional optimism/pessimism. The Johnson’s method was used for estimating the relative weight of predictor variables in multiple regression. Our results support that two dimensions of PEI (Clarity and Repair) are good predictors of SWB, whereas the third dimension, Emotional Attention, seems not adequate as a predicto

Psicothema

Resumen tomado de la publicaciónEl efecto de la deseabilidad en las medidas psicométricas de agresividad. Aunque numerosos estudios han analizado los efectos de la deseabilidad social en las medidas de personalidad, muy pocos se han centrado en los efectos de la misma en un comportamiento fuertemente reprobado por la sociedad como es la agresividad. El estudio que presentamos analiza el impacto de la deseabilidad social en las medidas de agresividad directa e indirecta, así como en sus relaciones con la impulsividad utilizando un método que permite obtener puntuaciones en los factores de contenido libres de los efectos de la deseabilidad social. Los resultados señalan que las medidas de agresividad se ven fuertemente afectadas por la deseabilidad social pero que las relaciones entre las mismas con la impulsividad se deben al contenido de agresividad de los tests y no a un factor común de deseabilidad social.AsturiasColegio Oficial de Psicólogos de Asturias; Calle Ildefonso Sánchez del Río, 4-1 B; 33001 Oviedo; Tel. +34985285778; Fax +34985281374;Universidad de Oviedo. Facultad de Psicología; Plaza Feijoo, s. n.; 33003 Oviedo; Tel. +34985104146; Fax +34985104126;ES

MultipleCar: A Graphical User Interface MATLAB Toolbox to Compute Multiple Correspondence Analysis

In this paper we present the toolbox MultipleCar, which was designed using a graphical user interface, a general program for computing Multiple Correspondence Analysis. The procedures implemented in MultipleCar are the usual ones that are already available in other applications, plus some additional procedures. MultipleCar makes it possible to compute (1) joint correspondence analysis, and (2) orthogonal and oblique rotation of coordinates. Although MultipleCar was developed in MATLAB, we compiled it as a standalone application for Windows operative systems based on graphical user interfaces. The users can decide whether to use the advanced MATLAB version of MultipleCar, or the standalone version (which does not require any programming skills)

Self-Assessment of Individual Differences in Language Switching

Language switching is omnipresent in bilingual individuals. In fact, the ability to switch languages (code switching) is a very fast, efficient, and flexible process that seems to be a fundamental aspect of bilingual language processing. In this study, we aimed to characterize psychometrically self-perceived individual differences in language switching and to create a reliable measure of this behavioral pattern by introducing a bilingual switching questionnaire. As a working hypothesis based on the previous literature about code switching, we decomposed language switching into four constructs: (i) L1 switching tendencies (the tendency to switch to L1; L1-switch); (ii) L2 switching tendencies (L2-switch); (iii) contextual switch, which indexes the frequency of switches usually triggered by a particular situation, topic, or environment; and (iv) unintended switch, which measures the lack of intention and awareness of the language switches. A total of 582 Spanish–Catalan bilingual university students were studied. Twelve items were selected (three for each construct). The correlation matrix was factor-analyzed using minimum rank factor analysis followed by oblique direct oblimin rotation. The overall proportion of common variance explained by the four extracted factors was 0.86. Finally, to assess the external validity of the individual differences scored with the new questionnaire, we evaluated the correlations between these measures and several psychometric (language proficiency) and behavioral measures related to cognitive and attentional control. The present study highlights the importance of evaluating individual differences in language switching using self-assessment instruments when studying the interface between cognitive control and bilingualism