FAKTORIJALNA INVARIJANTNOST U LONGITUDINALNIM STUDIJAMA: MERENJE ISTOG KONSTRUKTA TOKOM VREMENA
Ključne reči:
ponovljena merenja, konfirmativna faktorska analiza, faktorijalna invarijantnost, invarijantnost merenja
Sažetak
Neretko se u istraživanjima prilikom ponavljanog zadavanja istog instrumenta podrazumeva da će taj instrument jednako da meri pretpostavljeni latentni konstrukt koliko god puta da ga zadamo, odnosno da se njegova svojstva neće promeniti tokom vremena. Međutim, invarijatnost merenja nije nešto što instrument poseduje kao default, već je invarijatnost potrebno testirati. Cilj ovog rada se upravo ogleda prikazu načina na koji se primenom konfirmativne faktorske analize na setu longitudinalnih podataka može ispitati faktorijalna invarijatnost. Prvi deo rada je teorijski i predstavlja pregled različitih tipova invarijatnosti, dok je drugi deo rada zamišljen kao praktikum jer prikazuje na koji način se konfirmativna faktorska analiza za ponovljena merenja realizovana u softverskom okruženju R koristi za ispitivanje invarijatnosti.
Reference
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Raykov, T., & Amemiya, Y. (2008). Testing Time-Invariance of Variable Specificity in Repeated Measure Designs Using Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 15(3), 449–461. https://doi.org/10.1080/10705510802154315
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Widaman, K. F., Ferrer, E., & Conger, R. D. (2010). Factorial Invariance Within Longitudinal Structural Equation Models: Measuring the Same Construct Across Time. Child Development Perspectives, 4(1), 10–18. https://doi.org/10.1111/j.1750-8606.2009.00110.x
Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. The Science of Prevention: Methodological Advances from Alcohol and Substance Abuse Research, 281–324. https://doi.org/10.1037/10222-009
Carmines, E. G., & McIver, J. D. (1981). Analyzing models with unobserved variables: Analysis of covariance structures. U G. W. Bohinstedt & E. F. Borgatta (Eds.), Social measurement: Current issues (pp. 65 - 115). Sage.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1207/s15328007sem0902_5
Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9(2), 233–255.
Chungkham, H. S., Ingre, M., Karasek, R., Westerlund, H., & Theorell, T. (2013). Factor Structure and Longitudinal Measurement Invariance of the Demand Control Support Model: An Evidence from the Swedish Longitudinal Occupational Survey of Health (SLOSH). PLoS ONE 8(8): e70541. https://doi.org/10.1371/journal.pone.0070541
Hirschfeld, G. & von Brachel, R. (2014). Improving Multiple-Group confirmatory factor analysis in R – A tutorial in measurement invariance with continuous and ordinal indicators. Practical Assessment, Research & Evaluation, 19(7), 1-12. Available online: http://pareonline.net/getvn.asp?v=19&n=7
Hu, L., & Bentler, P., M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55. https://doi.org/10.1080/10705519909540118
Jovanović, V., Gavrilov-Jerković, V., Žuljević, D. i Brdarić, D. (2014). Psihometrijska evaluacija Skale depresivnosti, anksioznosti i stresa – 21 (DAS–21) na uzorku studenata u Srbiji. Psihologija, 47, 93–112. https://doi.org/10.2298/PSI1401093J
Kenny, D. A., Kaniskan, B., & McCoach, D. B. (2014). The Performance of RMSEA in Models With Small Degrees of Freedom. Sociological Methods & Research, 44(3), 486–507. https://doi.org/10.1177/0049124114543236
Kline, R. B. (2010). Principles and practice of structural equation modeling. Guilford.
Lovibond, S. H., Lovibond, P. F. (1995). Manual for the Depression Anxiety Stress Scales (2nd ed.). Psychology Foundation of Australia.
Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58(4), 525–543. https://doi.org/10.1007/bf02294825
Milfont, T. L., & Fischer, R. (2010). Testing measurement invariance across groups: Applications in cross-cultural research. International Journal of Psychological Research, 3(1), 111-130. https://doi.org/10.21500/20112084.857
Newsom, J. T. (2015). Longitudinal Structural Equation Modeling: A Comprehensive Introduction. Routledge.
Raykov, T., & Amemiya, Y. (2008). Testing Time-Invariance of Variable Specificity in Repeated Measure Designs Using Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 15(3), 449–461. https://doi.org/10.1080/10705510802154315
Raykov, T. & Marcoulides, G. A. (2006). A First Course in Structural Equation Modeling (2nd edition). Mahwah, NJ: Lawrence Erlbaum. https://doi.org/10.4324/9780203930687
Rosseel, Y. (2017). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. URL: http://www.jstatsoft.org/v48/i02/.
RStudio Team (2017). RStudio: Integrated Development for R. RStudio, Inc., Boston, MA. URL: http://www.rstudio.com/.
Vandenberg, R. J., & Lance, C. E. (2000). A Review and Synthesis of the Measurement Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research. Organizational Research Methods, 3(1), 4–70. https://doi.org/10.1177/109442810031002
Widaman, K. F., Ferrer, E., & Conger, R. D. (2010). Factorial Invariance Within Longitudinal Structural Equation Models: Measuring the Same Construct Across Time. Child Development Perspectives, 4(1), 10–18. https://doi.org/10.1111/j.1750-8606.2009.00110.x
Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. The Science of Prevention: Methodological Advances from Alcohol and Substance Abuse Research, 281–324. https://doi.org/10.1037/10222-009
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