Anales De Psicologia 

About: Anales De Psicologia is an academic journal published by Servicio de Publicaciones. The journal publishes majorly in the area(s): Psychology & Population. It has an ISSN identifier of 0212-9728. It is also open access. Over the lifetime, 1770 publications have been published receiving 26157 citations. The journal is also known as: Annals of psychology.

Un sistema de clasificación de los diseños de investigación en psicología

Abstract: Title: A classification system for research designs in psychology. Abstract: In this work we devise a conceptual framework and develop some basic principles to promove a classification system for the most usual research designs in psychology based on three strategies (manipulative, as- sociative and descriptive) from which emerge different types of studies, three for manipulative strategy (experimental, quasi-experimental and sin- gle-case), three for associative strategy (comparative, predictive and expla- natory) and two for descriptive strategy (observational and selective).

El Análisis Factorial Exploratorio de los Ítems: una guía práctica, revisada y actualizada

Abstract: Exploratory Factor analysis is one of the techniques used in the development, validation and adaptation of psychological measurement instruments Its use spread during the 1960s and has been growing exponentially thanks to the advancement of information technology The criteria used, of course, have also evolved But the applied researchers, who use this technique as a routine, remain often ignorant of all this In the last few decades numerous studies have denounced this situation There is an urgent need to update the classic criteria The incorporation of the most suitable criteria will improve the quality of our research In this work we review the classic criteria and, depending on the case, we also propose current criteria to replace or complement the former Our objective is to offer the interested applied researcher updated guidance on how to perform an Exploratory Item Factor Analysis, according to the “post-Little Jiffy” psychometrics This review and the guide with the corresponding recommendations have been articulated in four large blocks: 1) the data type and the matrix of association, 2) the method of factor estimation, 3) the number of factors to be retained, and 4) the method of rotation and allocation of items An abridged version of the complete guide is provided at the end of the article

Things i have learned (so far)

Abstract: This is an account of what I have learned (so far) about the application of statistics to psychology and the other sociobiomedical sciences. It includes the principles "less is more" (fewer variables, more highly targeted issues, sharp rounding off), "simple is better" (graphic representation, unit weighting for linear composites), and "some things you learn aren't so." I have learned to avoid the many misconceptions that surround Fisherian null hypothesis testing. I have also learned the importance of power analysis and the determination of just how big (rather than how statistically significant) are the effects that we study. Finally, I have learned that there is no royal road to statistical induction, that the informed judgment of the investigator is the crucial element in the interpretation of data, and that things take time.

A journey around alpha and omega to estimate internal consistency reliability

Abstract: Based on recent psychometric developments, this paper presents a conceptual and practical guide for estimating internal consistency reliability of measures obtained as item sum or mean. The internal consistency reliability coefficient is presented as a by-product of the measurement model underlying the item responses. A three-step procedure is proposed for its estimation, including descriptive data analysis, test of relevant measurement models, and computation of internal consistency coefficient and its confidence interval. Provided formulas include: (a) Cronbach’s alpha and omega coefficients for unidimensional measures with quantitative item response scales, (b) coefficients ordinal omega, ordinal alpha and nonlinear reliability for unidimensional measures with dichotomic and ordinal items, (c) coefficients omega and omega hierarchical for essentially unidimensional scales presenting method effects. The procedure is generalized to weighted sum measures, multidimensional scales, complex designs with multilevel and/or missing data and to scale development. Four illustrative numerical examples are fully explained and the data and the R syntax are provided.

Bienestar psicológico en estudiantes universitarios: facilitadores y obstaculizadores del desempeño académico

Abstract: Tittle: Psychological well-being among university students: facilitators and obstacles of academic performance Abstract: The quality of the service in the learning process is an important goal of Universities In this way, the identification of obstacles and facilita- tors of the learning process, as well as its relationship with subjective well- being and performance of students is a key topic Current research was done among 872 University students from Universitat Jaume I (Spain) from 18 different academic specialities of the three University centres Re- sults from self-report questionnaire and qualitative techniques (brainstorm- ing and focus groups), showed a positive relationship among academic obsta- cles, burnout and intention to leave On the other hand, academic facilita- tors are positively related with engagement, commitment, self-efficacy, satis- faction and happiness Regarding academic performance, we found gain and loss spirals among past success/failure, subjective (un/)well being, and future success/failure Finally, we proposed different intervention measures in order to reduce academic obstacles and optimise facilitators among students