Document Type
Article
Abstract
The impact of item parceling to improve model fit indexes in confirmatory factor analysis has been on debate amongst psychometricians. In this study, the effectiveness of item parceling was examined using Tes Potensi Akademik Pascasarjana (PAPS) or Postgraduate Academic Potential Test in Universitas Gadjah Mada. Item parceling approach, second-order approach, and item-based approach of confirmatory factor analysis (CFA) were used for examination. Data were collected from a sample of 1374 postgraduate candidates in 2017. The result found that model fit indices such as the chi-squared test, comparative fit index, Tucker-Lewis index, and standardized root mean square residual were improved in the item parceling approach when compared to item based approach. Interestingly, the root mean square error of approximation were deteriorating in the item parceling approach. The finding of this study suggested that model dimensionality and sample size should be carefully considered when using the item parceling approach.
First Page
26
Last Page
38
Issue
1
Volume
27
Digital Object Identifier (DOI)
10.21831/pep.v27i1.49012
Recommended Citation
Hapsari, Anindita Dwi and Widhiarso, Wahyu
(2023)
"The effectiveness of item parceling to increase the model fit: A case study of PAPs,"
Jurnal Penelitian dan Evaluasi Pendidikan: Vol. 27:
Iss.
1, Article 3.
DOI: 10.21831/pep.v27i1.49012
Available at:
https://scholarhub.uny.ac.id/jpep/vol27/iss1/3
References
Anderson, J. C., & Gerbing, D. W. (1984). The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika, 49(2), 155-173. https://doi.org/10.1007/bf02294170
Bainter, S. A., & Bollen, K. A. (2014). Interpretational confounding or confounded interpretations of causal indicators? Measurement: Interdisciplinary Research and Perspectives, 12(4), 125-140. https://doi.org/10.1080/15366367.2014.968503
Bandalos, D. L., & Finney, S. J. (2001). Item parceling issues in structural equation modeling. In G. A. Marcoulides & R. E. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 269-296). Lawrence Erlbaum Associates.
Bandalos, D. L. (1997). Assessing sources of error in structural equation models: The effects of sample size, reliability, and model misspecification. Structural Equation Modeling: A Multidisciplinary Journal, 4(3), 177-192. https://doi.org/10.1080/10705519709540070
Bandalos, D. L. (2002). The effects of item parceling on goodness-of-fit and parameter estimate bias in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 9(1), 78-102. https://doi.org/10.1207/s15328007sem0901_5
Bandalos, D. L. (2008). Is parceling really necessary? A comparison of results from item parceling and categorical variable methodology. Structural Equation Modeling: A Multidisciplinary Journal, 15(2), 211-240. https://doi.org/10.1080/10705510801922340
Bandalos, D. L. (2018). Measurement theory and applications for the social sciences. Guilford Press.
Bastos, J. L., Celeste, R. K., Faerstein, E., & Barros, A. J. (2010). Racial discrimination and health: A systematic review of scales with a focus on their psychometric properties. Social Science & Medicine, 70(7), 1091-1099. https://doi.org/10.1016/j.socscimed.2009.12.020
Belinda, B. (2015). Karakteristik psikometri tes PAPs seri A1. Undergraduate thesis, Universitas Gadjah Mada, Yogyakarta.
Birch, L., Fisher, J., Grimm-Thomas, K., Markey, C., Sawyer, R., & Johnson, S. (2001). Confirmatory factor analysis of the child feeding questionnaire: A measure of parental attitudes, beliefs and practices about child feeding and obesity proneness. Appetite, 36(3), 201-210. https://doi.org/10.1006/appe.2001.0398
Boomsma, A., & Hoogland, J. J. (2001). The robustness of LISREL modeling revisited. In R. Cudeck, S. du Toit, & D. Sörbom (Eds.), Structural equation modeling, present and future ER (Preliminary version, pp. 139-168). Scientific Software International.
Boomsma, A. (1985). Nonconvergence, improper solutions, and starting values in Lisrel maximum likelihood estimation. Psychometrika, 50(2), 229-242. https://doi.org/10.1007/bf02294248
Burisch, M. (1984). Approaches to personality inventory construction: A comparison of merits. American Psychologist, 39(3), 214-227. https://doi.org/10.1037//0003-066x.39.3.214
Burns, G. L., Boe, B., Walsh, J. A., Sommers-Flanagan, R., & Teegarden, L. A. (2001). A confirmatory factor analysis on the DSM-IV ADHD and ODD symptoms: What is the best model for the organization of these symptoms? Journal of Abnormal Child Psychology, 29, 339-349. https://doi.org/10.1023/A:1010314030025
Byrne, B. M. (2012). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge Academic.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 14(3), 464-504. https://doi.org/10.1080/10705510701301834
Chin, W. W. (1998). Commentary: Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), vii-xvi. http://www.jstor.org/stable/249674
Cole, D. A., Perkins, C. E., & Zelkowitz, R. L. (2015). Impact of homogeneous and heterogeneous parceling strategies when latent variables represent multidimensional constructs. Psychological Methods, 21(2), 164-174. https://doi.org/10.1037/met0000047
Cole, D. A., & Preacher, K. J. (2014). Manifest variable path analysis: Potentially serious and misleading consequences due to uncorrected measurement error. Psychological Methods, 19(2), 300-315. https://doi.org/10.1037/a0033805
De Bruin, G. P. (2004). Problems with the factor analysis of items: Solutions based on Item Response Theory and item parcelling. SA Journal of Industrial Psychology, 30(4). https://doi.org/10.4102/sajip.v30i4.172
Drolet, A. L., & Morrison, D. G. (2001). Do we really need multiple-item measures in service research? Journal of Service Research, 3(3), 196-204. https://doi.org/10.1177/109467050133001
Gatignon, H. (2016). Statistical analysis of management data. Springer.
Hair, J. F. (2019). Multivariate data analysis. Cengage.
Hancock, G. R. (2003). Fortune cookies, measurement error, and experimental design. Journal of Modern Applied Statistical Methods, 2(2), 293-305. https://doi.org/10.22237/jmasm/1067644980
Holbert, R. L., & Stephenson, M. T. (2002). Structural equation modeling in the communication sciences, 1995-2000. Human Communication Research, 28(4), 531-551. https://doi.org/10.1111/j.1468-2958.2002.tb00822.x
Hooper, D., Mullen, M. R., & Coughlan, J. (2008). Structural equation modeling: Guidelines for determining model fit. Electronic Journal on Business Research Methods, 6(1), 53-60. https://doi.org/10.21427/D7CF7R
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
Jackson, D. L. (2001). Sample size and number of parameter estimates in maximum likelihood confirmatory factor analysis: A Monte Carlo investigation. Structural Equation Modeling: A Multidisciplinary Journal, 8(2), 205-223. https://doi/.org/10.1207/S15328007SEM0802_3
Kenny, D. A. (1979). Correlation and causality. Wiley.
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. (2016). Principles and practice of structural equation modeling. Guilford Press.
Kolenikov, S., & Bollen, K. A. (2012). Testing negative error variances. Sociological Methods & Research, 41(1), 124-167. https://doi.org/10.1177/0049124112442138
Ladhari, R. (2010). Developing e-service quality scales: A literature review. Journal of Retailing and Consumer Services, 17(6), 464-477. https://doi.org/10.1016/j.jretconser.2010.06.003
Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to parcel: Exploring the question, weighing the merits. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 151-173. https://doi.org/10.1207/s15328007sem0902_1
Marsh, H. W., Hau, K., & Grayson, D. (2005). Goodness of fit in structural equation models. In Contemporary psychometrics: A festschrift for Roderick P. McDonald (pp. 275-340). Lawrence Erlbaum Associates.
Marsh, H. W., Hau, K.-T., Balla, J. R., & Grayson, D. (1998). Is more ever too much? The number of indicators per factor in confirmatory factor analysis. Multivariate Behavioral Research, 33(2), 181-220. https://doi.org/10.1207/s15327906mbr3302_1
Marsh, H. W., & Hau, K.-T. (2004). Explaining paradoxical relations between academic self-concepts and achievements: Cross-cultural generalizability of the internal/external frame of reference predictions across 26 countries. Journal of Educational Psychology, 96(1), 56-67. https://doi.org/10.1037/0022-0663.96.1.56
Marsh, H. W., Lüdtke, O., Robitzsch, A., Trautwein, U., Asparouhov, T., Muthén, B., & Nagengast, B. (2009). Doubly-latent models of school contextual effects: Integrating multilevel and structural equation approaches to control measurement and sampling error. Multivariate Behavioral Research, 44(6), 764-802. https://doi.org/10.1080/00273170903333665
Marsh, H. W. (2012). Application of confirmatory factor analysis and structural equation modeling in sport and exercise psychology. In G. Tenenbaum, R. C. Eklund (Eds.), Handbook of sport psychology (pp. 774-798). Wiley. https://doi.org/10.1002/9781118270011.ch35
Matsunaga, M. (2008). Item parceling in structural equation modeling: A primer. Communication Methods and Measures, 2(4), 260-293. https://doi.org/10.1080/19312450802458935
McDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64-82. https://doi.org/10.1037/1082-989x.7.1.64
McGrath, R. E. (2005). Conceptual complexity and construct validity. Journal of Personality Assessment, 85(2), 112-124. https://doi.org/10.1207/s15327752jpa8502_02
Myers, N. D., Ahn, S., & Jin, Y. (2011). Sample size and power estimates for a confirmatory factor analytic model in exercise and sport. Research Quarterly for Exercise and Sport, 82(3), 412-423. https://doi.org/10.1080/02701367.2011.10599773
Nasser, F., & Wisenbaker, J. (2003). A Monte Carlo study investigating the impact of item parceling on measures of fit in confirmatory factor analysis. Educational and Psychological Measurement, 63(5), 729-757. https://doi.org/10.1177/0013164403258228
Orcan, F. (2013). Use of item parceling in structural equation modeling with missing data. Doctoral dissertation, Florida State University.
Reilly, T. (1995). A necessary and sufficient condition for identification of confirmatory factor analysis models of factor complexity one. Sociological Methods & Research, 23(4), 421-441. https://doi.org/10.1177/0049124195023004002
Rhemtulla, M. (2016). Population performance of SEM parceling strategies under measurement and structural model misspecification. Psychological Methods, 21(3), 348-368. https://doi.org/10.1037/met0000072
Roberson, L. L., Aneni, E. C., Maziak, W., Agatston, A., Feldman, T., Rouseff, M., €¦ Nassir, K. (2014). Beyond BMI: The "Metabolically healthy obese" phenotype & its association with clinical/subclinical cardiovascular disease and all-cause mortality - A systematic review. BMC Public Health, 14(1), 14. https://doi.org/10.1186/1471-2458-14-14
Suhr, D. D. (2003). Exploratory or confirmatory factor analysis?. Statistics and Data Analysis, 200-31. https://support.sas.com/resources/papers/proceedings/proceedings/sugi31/200-31.pdf
Widhiarso, W. (2019). Pembuktian validitas terkait struktur tes potensi akademik pascasarjana (PAPS) Universitas Gadjah Mada. Jurnal Psikologi, 46(2), 145-162. https://doi.org/10.22146/jpsi.38223
Widhiarso, W., & Ravand, H. (2014). Estimating reliability coefficient for multidimensional measures - A pedagogical illustration. Review of Psychology, 21(2), 111-121. https://core.ac.uk/download/pdf/33286765.pdf
Widhiarso, W., Azwar, S., Suhapti, R., & Haryanta. (2015). Analisis dan penyempurnaan aitem-aitem tes PAPs seri A1. Seri Technical Report UPAP, 2(2), 1-7.
Wilkinson, T. J. (2007). Assessment of clinical performance: Gathering evidence. Internal Medicine Journal, 37(9), 631-636. https://doi.org/10.1111/j.1445-5994.2007.01483.x
Wongpakaran, T., Wongpakaran, N., Sirirak, T., Arunpongpaisal, S., & Zimet, G. (2017). Confirmatory factor analysis of the revised version of the Thai multidimensional scale of perceived social support among the elderly with depression. Aging & Mental Health, 22(9), 1149-1154. https://doi.org/10.1080/13607863.2017.1339778