Resumen
Antecedentes: La ansiedad estadística es un problema habitual en los estudiantes que cursan materias relacionadas con la estadística en las ciencias sociales. Una de las escalas más utilizadas en su evaluación es la Escala de Ansiedad Estadística. En algunas adaptaciones se han detectado problemas en la replicación de su estructura factorial y no controlan los sesgos de respuesta. El objetivo de nuestra investigación fue proponer un test para la evaluación de la ansiedad estadística incluyendo una escala para el control de la deseabilidad social. Método: Se desarrolló una versión revisada de la escala utilizando procedimientos para el control de la deseabilidad social analizándose su estructura factorial en una muestra de 531 estudiantes. Resultados: La versión revisada mostró un ajuste adecuado tanto a nivel exploratorio como confirmatorio a una estructura de cuatro factores; los tres de contenido esperados y un factor de deseabilidad social. Las escalas no mostraron efectos de la aquiescencia y un moderado efecto de la deseabilidad social, además las escalas de contenido mostraron una clara relación con el rendimiento académico. Conclusiones: La versión revisada de la escala mejora las propiedades de la versión precedente y puede solventar los problemas detectados en algunas adaptaciones de la misma.
Citas
Cantinotti, M., Lalande, D., Ferlatte, M. A., & Cousineau, D. (2017). Validation de la version francophone du Questionnaire d’anxiété statistique (SAS-F-24) [Validation of the French version of the statistical anxiety scales]. Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 49(2), 133–142. https://dx.doi.org/10.1037/cbs0000074
Chew, P. K., & Dillon, D. B. (2014a). Reliability and validity of the Statistical Anxiety Scale among students in Singapore and Australia. Journal of Tropical Psychology, 4(e7), 1-14. https://doi.org/10.1017/jtp.2014.7
Chew, P. K., & Dillon, D. B. (2014b). Statistics anxiety update: Refining the construct and recommendations for a new research agenda. Perspectives on Psychological Science, 9(2), 196-208. https://doi.org/10.1177/1745691613518077
Chiesi, F., Primi, C., & Carmona, J. (2011). Measuring statistics anxiety: Cross-country validity of the Statistical Anxiety Scale (SAS). Journal of psychoeducational assessment, 29(6), 559-569. https://doi.org/10.1177/0734282911404985
Cui, S., Zhang, J., Guan, D., Zhao, X., & Si, J. (2019). Antecedents of statistics anxiety: An integrated account. Personality and Individual Differences, 144, 79-87. https://doi.org/10.1016/j.paid.2019.02.036
Cruise, R. J., Cash, R. W., & Bolton, D. L. (1985). Development and validation of an instrument to measure statistical anxiety. American Statistical Association Proceedings of the Section on Statistical Education, 4(3), 92-97.
Durak, I., & Karagöz, Y. (2021). Adaptation of Statistics Anxiety Scale to Turkish: Validity and Reliability Study. International Journal of Assessment Tools in Education, 8(3), 667-683. https://doi.org/10.21449/ijate.863225
Ferrando, P.J., & Lorenzo-Seva, U. (2005). IRT-related factor analytic procedures for testing the equivalence of paper-and-pencil and Internet administered questionnaires. Psychological Methods, 10(2), 193-205. https://doi.org/10.1037/1082-989X.10.2.193
Ferrando, P. J., & Lorenzo-Seva, U. (2014). Exploratory item factor analysis: Additional considerations. Anales de psicología, 30(3), 1170- 1175.
https://doi.org/10.6018/analesps.30.3.199991
Ferrando, P. J., & Lorenzo-Seva U. (2016). A note on improving EAP trait estimation in oblique factor-analytic and item response theory models. Psicologica, 37(2), 235-247.
Ferrando, P.J., & Lorenzo-Seva, U. (2017). Program FACTOR at 10: origins, development and future directions. Psicothema, 29(2), 236-241. https://doi.org/10.7334/psicothema2016.304
Ferrando, P. J., & Lorenzo-Seva U. (2018). Assessing the quality and appro- priateness of factor solutions and factor score estimates in exploratory item factor analysis. Educational and Psychological Measurement, 78(5), 762-780. https://doi.org/10.1177/0013164417719308
Ferrando, P. J., & Lorenzo-Seva, U. (2021). The Appropriateness of Sum Scores as Estimates of Factor Scores in the Multiple Factor Analysis of Ordered-Categorical Responses. Educational and Psychological Measurement, 81(2), 205-228. https://doi.org/10.1177/0013164420938108
Ferrando, P. J., Lorenzo-Seva, U., & Chico, E. (2009). A general factor- analytic procedure for assessing response bias in questionnaire measures. Structural Equation Modeling: A Multidisciplinary Journal, 16(2), 364-381. https://doi.org/10.1080/10705510902751374
Ferrando, P. J., Lorenzo-Seva, U., Hernández-Dorado, A., & Muñiz, J. (2022). Decalogue for the Factor Analysis of Test Items. Psicothema, 34(1), 7-17.
https://doi.org/10.7334/psicothema2021.456
Frey-Clark, M., Natesan, P., & O’Bryant, M. (2019). Assessing statistical anxiety among online and traditional students. Frontiers in Psychology, 10, Article 1440.
https://doi.org/10.3389/fpsyg.2019.01440
Hernandez, J. A. E., Santos, G. R. D., Silva, J. D. O. D., Mendes, S. L. L., & Ramos, V. D. C. B. (2015). Validity of the Statistics Anxiety Scale in Psychology Students. Psicologia: Ciência e profissão, 35(3), 659-675. https://doi.org/10.1590/1982-3703000362014
Hernández-Dorado, A., Vigil-Colet, A., Lorenzo-Seva, U., & Ferrando, P. J. (2021). Is correcting for acquiescence increasing the external validity of personality test scores? Psicothema, 33(4), 639-646. https://doi.org/10.7334/psicothema2021.131
Holden, R. (2010). Social desirability. Corsini Encyclopedia of Psychology.
John Wiley & Sons, Inc. Johnson, T., Kulesa, P., Cho, Y. I., & Shavitt, S. (2005). The relation between culture and response styles: Evidence from 19 countries. Journal of Cross-cultural psychology, 36(2), 264-277. https://doi.org/10.1177/0022022104272905
Leite, W.L., & Cooper, L.A. (2010). Detecting social desirability bias using factor mixture models. Multivariate Behavioral Research, 45(2), 271- 293. https://doi.org/10.1080/00273171003680245
Li, A., & Bagger, J. (2006). Using the BIDR to distinguish the effects of impression management and self-deception on the criterion validity of personality measures: A meta-analysis. International Journal of Selection & Assessment, 14(2), 131-141. https://doi.org/10.1111/j.1468-2389.2006.00339.x
Lord, F. (1952). A theory of test scores. Psychometric Monographs 7.
Lorenzo-Seva, U. (2021). SOLOMON: a method for splitting a sample into equivalent subsamples in factor analysis. Behavior Research Methods. https://doi.org/10.3758/s13428-021-01750-y
Lorenzo‐Seva, U., & Ferrando, P. J. (2009). Acquiescent responding in partially balanced multidimensional scales. British Journal of Mathematical and Statistical Psychology, 62(2), 319-326. https://doi.org/10.1348/000711007X265164
Lorenzo-Seva, U., & Ferrando, P.J. (2019). Robust Promin: a method for diagonally weighted factor rotation. LIBERABIT, Revista Peruana de Psicología, 25, 99-106. https://doi.org/10.24265/liberabit.2019.v25n1.08
Lorenzo-Seva, U., & Ferrando, P. J. (2021a). Not positive definite correlation matrices in exploratory item factor analysis: causes, consequences and a proposed solution. Structural Equation Modeling: A Multidisciplinary Journal, 28(1), 138-147. https://doi.org/10.1080/10705511.2020.1735393
Lorenzo-Seva, U., & Ferrando, P. J. (2021b). MSA: The Forgotten Index for Identifying Inappropriate Items Before Computing Exploratory Item Factor Analysis. Methodology, 17(4), 296-306. https://doi.org/10.5964/meth.7185
Lorenzo-Seva, U., Timmerman, M. E., & Kiers, H.A.L. (2011). The Hull method for selecting the number of common factors. Multivariate Behavioral Research, 46(2), 340-364. https://doi.org/10.1080/00273171.2011.564527
Muthén L.K. & Muthén, B.O. (2007). Mplus user’s guide (5th Ed.). Muthén & Muthén.
Navarro-González, D., Lorenzo-Seva, U., & Vigil-Colet, A. (2016). How response bias affects the factorial structure of personality self-reports. Psicothema, 28(4), 465-470. https://doi.org/10.7334/psicothema2016.113
Navarro-González, D., Vigil-Colet, A., Ferrando, P. J., & Lorenzo-Seva, U. (2019). Psychological Test Toolbox: A New Tool to Compute Factor Analysis Controlling Response Bias. Journal of Statistical Software, 91(6), 1-21. https://doi.org/10.18637/jss.v091.i06
O’Bryant, M. J. (2017). How attitudes towards statistics courses and the field of statistics predicts statistics anxiety among undergraduate social science majors: a validation of the Statistical Anxiety Scale. [Doctoral dissertation, University of North Texas]. ProQuest Dissertations & Theses Global. https://search.proquest.com/docview/2009455494
O’Bryant, M., Natesan Batley, P., & Onwuegbuzie, A. J. (2021). Validation of an Adapted Version of the Statistical Anxiety Scale in English and Its Relationship to Attitudes Toward Statistics. SAGE Open, 11(1), 1-15. https://doi.org/10.1177/21582440211001378
Oliver, A., Sancho, P., Galiana, L., & Cebrià i Iranzo, M. A. (2014). Nueva evidencia sobre la Statistical Anxiety Scale (SAS) [New evidence on the Statistical Anxiety Scale (SAS)]. Anales de psicología, 30(1), 150-156. https://doi.org/10.6018/analesps.30.1.151341
Onwuegbuzie, A. J., Da Ros, D., & Ryan, J. (1997). The components of statistics anxiety: A phenomenological study. Focus on Learning Problems in Mathematics, 19(4), 11-35.
Onwuegbuzie, A. J., & Wilson, V. (2003). Statistics anxiety: Nature, etiology antecedents, effects, and treatments—A comprehensive review of the literature. Teaching in Higher Education, 8(2), 195-209. https://doi.org/10.1080/1356251032000052447
Paul, L., Parveen, T., Ahmed, O., & Aktar, R. (2018). Adaptation study of the statistical anxiety scale on a Bangladeshi sample. Bulgarian Journal of Science & Education Policy, 12(2), 380-401.
Paulhus D.L. (1991). Measurement and Control of Response Bias. In J. P. Robinson, P. R. Shaver, & L. S. Wright (Eds.), Measures of personality and social psychological attitudes (pp. 17-59). Academic Press.
Paulhus, D. L., & Vazire, S. (2005). The Self-Report Method. In R. W. Robins, R. Fraley & R. F. Krueger (Eds.). Handbook of research methods in personality psychology (pp. 224-239). Guilford Press.
Rammstedt, B., & Farmer, R. F. (2013). The impact of acquiescence on the evaluation of personality structure. Psychological Assessment, 25(4),1137-1145.
https://doi.org/10.1037/a0033323
Soubelet, A., & Salthouse, T.A. (2011). Influence of social desirability on age differences in self-reports of mood and personality. Journal of Personality, 79(4), 741-762. https://doi.org/10.1111/j.1467-6494.2011.00700.x
Steinberger, P. (2020). Assessing the statistical anxiety rating scale as applied to prospective teachers in an Israeli teacher-training college. Studies in Educational Evaluation, 64, Article 100829. https://doi.org/10.1016/j.stueduc.2019.100829
Vigil-Colet, A., Lorenzo-Seva, U., & Condon, L. (2008). Development and validation of the statistical anxiety scale. Psicothema, 20(1), 174–180.
Vigil-Colet, A., Morales-Vives, F., Camps, E., Tous, J., & Lorenzo-Seva, U. (2013). Development and validation of the Overall Personality Assessment Scale (OPERAS). Psicothema, 25(1), 100-106. https://doi.org/10.7334/psicothema2011.411
Vigil-Colet,A., Navarro-González, D., & Morales-Vives, F. (2020).To reverse or to not reverse Likert-type items: That is the question. Psicothema, 32(1), 108-114.
https://doi.org/10.7334/psicothema2019.286
Zeidner, M. (1991). Statistics and mathematics anxiety in social science students: Some interesting parallels. British journal of educational psychology, 61(3), 319-328. https://doi.org/10.1111/j.2044-8279.1991.tb00989.x