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Invariance of Socioeconomic Status Scales in International Studies

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Validity of Educational Assessments in Chile and Latin America

Abstract

We use data from the international assessments PISA, TERCE, and ICCS to evaluate the invariance of student socioeconomic background scales among the countries participating in these studies. More specifically, we examine whether measures that were developed regionally exhibit better psychometric properties than other measures that were designed to work in a larger and more diverse number of education systems. First, we test the invariance of socioeconomic status (SES) scales across all the countries participating in each study, and then, we run the same test including only Latin American countries. The results suggest that none of the SES scales are invariant at the scalar level among all the countries participating in each study, and therefore comparisons between nations should be made with caution. As for the second group of analyses, our results show that when the analysis is restricted to Latin American countries, the invariance levels improve considerably. Finally, the levels of invariance achieved by each scale in each study and for each group of countries are discussed, as well as the type of comparisons that can be made given these results.

The support of the Center for Advanced Studies on Educational Justice (CONICYT PIA CIE160007) for the funding for the research and writing of this chapter is appreciated.

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References

  • American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for educational and psychological testing. American Educational Research Association.

    Google Scholar 

  • Bentler, P. M. (1982). Confirmatory factor analysis via non-iterative estimation. A fast, inexpensive method. Journal of Marketing Research, 19(4), 417–424.

    Google Scholar 

  • Billiet, J. (2003). Cross-cultural equivalence with structural equation modeling. In J. Harkness, F. van de Vijver, & P. Mohler (Eds.), Cross-cultural survey methods (pp. 247–264). Wiley.

    Google Scholar 

  • Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). Guildford Press.

    Google Scholar 

  • Buchmann, C. (2002). Measuring family background in international studies of education: Conceptual issues and methodological challenges. In A. C. Porter & A. Gamoran (Eds.), Methodological advances in cross-national surveys of educational achievement (pp. 150–197). National Academy Press.

    Google Scholar 

  • Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255. https://doi.org/10.1207/S15328007SEM0902_5

    Article  Google Scholar 

  • Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological test. Psychological Bulletin, 52(4), 281–302. https://doi.org/10.1037/h0040957

    Article  Google Scholar 

  • Erberber, E., Stephens, M., Mamedova, S., Ferguson, S., & Kroeger, T. (2015). Socioeconomically disadvantaged students who are academically successful: examining academic resilience cross-nationally. IEA Policy Brief Series (No.5). IEA. Retrieved from http://www.iea.nl/policy_briefs.html

  • Glas, C., & Jehangir, K. (2014). Modeling country-specific differential item functioning. In L. Rutkowski, M. von Davier, & D. Rutkowski (Eds.), Handbook of international large-scale assessment: Background, technical issues, and methods of data analysis. Chapman & Hall/CRC Press.

    Google Scholar 

  • Jöreskog, K. G. (1971). Simultaneous factor analysis in several populations. Psychometrika, 36(4), 408–426.

    Article  Google Scholar 

  • Marsh, H. W., Ludtke, O., Muthen, B., Asparouhov, T., Morin, A. J. S., & Trautwein, U. (2010). A new look at the big five factor structure through exploratory structural equation modeling. Psychological Assessment, 22(3), 471–491. https://doi.org/10.1037/a0019227

    Article  Google Scholar 

  • McGrath, R. E. (2015). Measurement invariance in translations of the VIA inventory of strengths. European Journal of Psychological Assessment, 32, 187–194. https://doi.org/10.1027/1015-5759/a000248

  • Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in test of measurement invariance. The Journal of Applied Psychology, 93(3), 568–592. https://doi.org/10.1037/0021-9010.93.3.568

    Article  Google Scholar 

  • Meredith, W. (1993). Measurement invariance, factor analysis and factor invariance. Psychometrika, 58, 525–543.

    Article  Google Scholar 

  • Messick, S. (1984). The psychology of educational measurement. Journal of Educational Measurement, 21(3), 215–237.

    Article  Google Scholar 

  • Mullis, I. V. S., Martin, M. O., Foy, P., & Hooper, M. (2016). TIMSS 2015 International results in mathematics. TIMSS & PIRLS International Study Center/IEA

    Google Scholar 

  • Organization for Economic Cooperation and Development. (2011). Against the odds: Disadvantaged students who succeed in school. OECD Publishing.

    Google Scholar 

  • Organization for Economic Cooperation and Development. (2014). PISA 2012 Technical report. OECD Publishing.

    Google Scholar 

  • Organization for Economic Cooperation and Development. (2016a). PISA 2015 background questionnaires. In PISA (pp. 129–196). OECD Publishing. Retrieved from http://www.OCDE-ilibrary.org/content/chapter/9789264255425-8-en

  • Organization for Economic Cooperation and Development. (2016b). PISA 2015 Assessment and analytical framework. OECD Publishing. Retrieved from http://www.OCDE-ilibrary.org/content/book/9789264255425-en

  • Oliveri, M. E., & von Davier, M. (2011). Research of model fit and score scale comparability in international assessments. Psychological Test and Assessment Modeling, 53(3), 315–333.

    Google Scholar 

  • Oliveri, M. E., & von Davier, M. (2014). Toward increasing fairness in score scale calibrations employed in international large-scale assessments. International Journal of Testing, 14(1), 1–21. https://doi.org/10.1080/15305058.2013.825265

    Article  Google Scholar 

  • Rutkowski, L., & Svetina, D. (2014). Assessing the hypothesis of measurement invariance in the context of large-scale international surveys. Educational and Psychological Measurement, 74(1), 31–57. https://doi.org/10.1177/0013164413498257

    Article  Google Scholar 

  • Sandoval-Hernandez, A., Rutkowski, D., Matta, T., & Miranda, D. (2019). Back to the drawing board: Can we compare socioeconomic background scales? Revista de Educación, 383, 37–61. https://doi.org/10.4438/1988-592X-RE-2019-383-400

  • Schulz, W., Ainley, J., & Fraillon, J. (Eds.). (2011). ICCS 2009 Technical report. IEA.

    Google Scholar 

  • Schulz, W., Carstens, R., Losito, B., & Fraillon, J. (Eds.). (2018). ICCS 2016 Technical report. Amsterdam, Netherlands: IEA.

    Google Scholar 

  • Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin Company.

    Google Scholar 

  • Traynor, A., & Raykov, T. (2013). Household possessions indices as wealth measures: A validity evaluation. Comparative Education Review, 57(4), 662–688. https://doi.org/10.1086/671423

    Article  Google Scholar 

  • Treviño, E., Fraser, P., Meyer, A., Morawietz, L., Inostroza, P., & Naranjo, E. (2015). TERCE results report: Associated factors. OREAL/UNESCO.

    Google Scholar 

  • UNESCO-OREALC. (2016). Technical report: Third regional comparative and explanatory study, TERCE. OREAL/UNESCO.

    Google Scholar 

  • Van Der Linden, W. J. (2005). A comparison of item-Selection methods for adaptive test with content constraints. Journal of Educational Measurement, 42(3), 283–302.

    Article  Google Scholar 

  • Wilson, M. (2005). Constructing measures: An item response modeling approach. Lawrence Erlbaum Associates.

    Google Scholar 

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Correspondence to Andrés Sandoval-Hernández .

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Treviño, E., Sandoval-Hernández, A., Miranda, D., Rutkowski, D., Matta, T. (2021). Invariance of Socioeconomic Status Scales in International Studies. In: Manzi, J., García, M.R., Taut, S. (eds) Validity of Educational Assessments in Chile and Latin America. Springer, Cham. https://doi.org/10.1007/978-3-030-78390-7_10

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  • DOI: https://doi.org/10.1007/978-3-030-78390-7_10

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