Background: The study of entrepreneurial activity has undergone intense development in recent decades. Traditionally this topic has been addressed from three approaches: economic, sociological and psychological. In the study of enterprising personality, two fundamental perspectives stand out: the use of general personality traits, like the Big Five, and the use of more specific traits related to entrepreneurial spirit, such as self-efficacy, autonomy, innovation, optimism, and others. The objective of this study is to provide validity evidence for a new instrument for measuring eight specific dimensions of entrepreneurial personality (BEPE).Methods: The sample was composed of 1,170 adults from the general population (59.9% women). The average age was 42.34 years with a standard deviation of 12.96. Of the sample, 13% were self-employed. Internal factorial structure and reliability of BEPE were examined. The relationships with other variables and the discriminative capacity of the BEPE between different groups of workers were analyzed.Results: First order exploratory factor analyses show the essential unidimensionality of each of the eight proposed sub-scales, with factorial weights ranging between 0.341 and 0.825. In the Confirmatory Factor Analysis, the best fit was achieved with a Bifactor model. With regards to reliability, the eight BEPE sub-scales gave high alpha coefficient values, between 0.81 and 0.89, as did the total battery (0.97). BEPE sub-scales show a high canonical correlation with the Big Five personality factors (0.796) and with the sub-scales of the Measure of Entrepreneurial Talents and Abilities questionnaire (0.779).Conclusion: The BEPE questionnaire for the evaluation of the eight fundamental specific dimensions of the entrepreneurial personality presents adequate psychometric properties. Its relationships with other measures of personality traits are in line with what is expected. Therefore, the BEPE is a new measurement instrument that can be used with confidence both in the applied field and in research.

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The relationship between homework and academic results has been widely researched. Most of that research has used English-speaking, European or Asian samples, and to date there have been no detailed studies into that relationship in Latin America and the Caribbean. The aim of this study is to examine the effect of quantitative homework characteristics on achievement in science. The sample comprised 61,938 students at 2,955 schools in the 15 Latin American countries (plus the Mexican state of New Leon) which participated in the Third Regional Comparative and Explanatory Study (TERCE), carried out by the Latin American Laboratory for Educational Quality (LLECE) in 2013. The mean age was 12.42 years old (±0.94). Within each country, three hierarchical-linear models were applied at two levels: student and school. The individual level considered time spent doing homework and the school level considered the amount and frequency of homework assignment. In addition, ten control variables were included in order to control the net effect of the characteristics of the homework on the result. The results confirmed that homework is widely assigned in the Latin American region. At the individual level, time spent on homework had little effect on academic performance, while in the quantitative homework characteristics it was the frequency of homework assignment which demonstrated a clearer effect rather than the amount of homework assigned.

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Resumen: Se investigó la influencia que tienen los valores perdidos sobre la estimación de las propiedades psicométricas de los tests de personalidad. Se ha utilizado un enfoque aplicado, simulando situaciones que puedan tener relevancia cara a la práctica profesional. Se diseñaron dos estudios de simulación a partir de datos reales obtenidos de la aplicación de la prueba ESQUIZO-Q que evalúa esquizotipia. En el primero de ellos se utilizó una muestra de 3056 personas y en el segundo una de 200; en ambos casos se emplearon cuatro niveles de pérdida de respuestas y ocho procedimientos de imputación de los valores perdidos. Se estudió su influencia sobre las estimaciones del coeficiente α de Cronbach, la estructura factorial de la prueba y la ordenación de las puntuaciones en el cuestionario. Los resultados apuntan a que en presencia de niveles bajos de valores perdidos, incluso los métodos más simples, ofrecen soluciones muy razonables desde el punto de vista práctico. Desde la perspectiva más estadística el procedimiento de Expectación-Maximización (EM) es el que presenta un mejor comportamiento global en los diferentes criterios manejados. Destaca también el pobre comportamiento de los métodos de sustitución por el valor anterior o posterior de cara a mantener la estructura factorial de los datos. Palabras clave: Valores perdidos; fiabilidad; personalidad; imputación.Title: Missing data and psychometric properties of personality tests. Abstract: The aim of this study was to analyze the influence of missing values on the psychometric properties of personality tests. An applied approach was used, trying to simulate conditions similar to those found in the professional practice. Two simulation studies were designed, based on actual data from the administration of ESQUIZO-Q test, which assesses schizotypy. In the first study a large sample was used (N=3056), and in the second one a smaller sample (N=200) was analyzed. In both cases four levels of missing values, and eight procedures for handling missing values were simulated. The influence of these conditions on the estimates of Cronbach's α, the factor structure of the test, and the arrangement of test scores were analyzed. The results suggest that in the presence of low levels of missing values, even the simplest imputation methods offer appropriate solutions from a applied point of view. From a statistical perspective the Expectation-Maximization (EM) method is the one with a better overall performance in the different criteria handled. Also noteworthy is the poor performance of replacement procedures when using the value of the previous or posterior item in order to maintain the factor structure of the data. Key words: Missing values; reliability; personality; imputation. IntroducciónAunque la mejor solución al problema de los datos perdidos sería no tenerlos (Allison, 2002), lo cierto es que tarde o temprano cualquier investigador que maneje datos empíricos acaba encontrándose con el problema. Tal y como indican van der Ark y Vermunt (2010), ignorar el problem...