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, 155–173. https://doi.org/10.1007/BF02294170
- Bagozzi, R. P., & Heatherton, T. F. (1994). A general approach to representing multifaceted personality constructs: Application to state self-esteem. Structural Equation Modeling, 1, 35–67. https://doi.org/10.1080/10705519409539961
- Bandalos, D. L. (2002). The effects of item parceling on goodness-of-fit and parameter estimate bias in structural equation modeling. Structural Equation Modeling, 9, 78–102. https://doi.org/10.1207/S15328007SEM0901
- Bandalos, D. L. (2008). Is parceling really necessary? A comparison of results from item parceling and categorical variable methodology. Structural Equation Modeling, 15, 211–240. https://doi.org/10.1080/10705510801922340
- Bandalos, D. L., & Finney, S. J. (2001). Item parceling issues in structural equation modeling. New Developments and Techniques in Structural Equation Modeling, 269, V296. https://doi-org.ezproxy.lib.utexas.edu/10.4324/9781410601858
- Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246. https://doi.org/10.1037/0033-2909.107.2.238
- Byrne, B. M. (2008). Testing for multigroup equivalence of a measuring instrument: A walk through the process. Psicothema, 20, 872–882.
- Byrne, B. M. (2013). Structural equation modeling with mplus: Basic concepts, applications, and programming. Routledge.
- Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105, 456–466. https://doi.org/10.1037/0033-2909.105.3.456
- Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14, 464–504. https://doi.org/10.1080/10705510701301834
- Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling, 9, 233–255. https://doi.org/10.1207/S15328007SEM0902_5
- Finch, W. H., & French, B. F. (2018). A simulation investigation of the performance of invariance assessment using equivalence testing procedures. Structural Equation Modeling, 25, 673–686. https://doi.org/10.1080/10705511.2018.1431781
- Hagtvet, K. A., & Nasser, F. M. (2004). How well do item parcels represent conceptually defined latent constructs? A two-facet approach. Structural Equation Modeling, 11, 168–193. https://doi.org/10.1207/s15328007sem1102_2
- Hall, R. J., Snell, A. F., & Foust, M. S. (1999). Item parceling strategies in SEM investigating the subtle effects of unmodeled secondary constructs. Organizational Research Methods, 2, 233–256. https://doi.org/10.1177/109442819923002
- Hancock, G. R. (1997). Structural equation modeling methods of hypothesis testing of latent variable means. Measurement and Evaluation in Counseling and Development, 30, 91. https://doi.org/10.1080/07481756.1997.12068926
- Hancock, G. R. (2001). Effect size, power, and sample size determination for structured means modeling and mimic approaches to between-groups hypothesis testing of means on a single latent construct. Psychometrika, 66, 373–388. https://doi.org/10.1007/BF02294440
- Hancock, G. R., Lawrence, F. R., & Nevitt, J. (2000). Type I error and power of latent mean methods and manova in factorially invariant and noninvariant latent variable systems. Structural Equation Modeling, 7, 534–556. https://doi.org/10.1207/S15328007SEM0704_2
- Hau, K.-T., & Marsh, H. W. (2004). The use of item parcels in structural equation modelling: Non-normal data and small sample sizes. British Journal of Mathematical and Statistical Psychology, 57, 327–351. https://doi.org/10.1111/j.2044-8317.2004.tb00142.x
- Holbert, R. L., & Stephenson, M. T. (2002). Structural equation modeling in the communication sciences, 1995–2000. Human Communication Research, 28, 531–551. https://doi.org/10.1111/j.1468-2958.2002.tb00822.x
- Hoogland, J. J., & Boomsma, A. (1998). Robustness studies in covariance structure modeling: An overview and a meta-analysis. Sociological Methods & Research, 26, 329–367. https://doi.org/10.1177/0049124198026003003
- Horn, J. L., & McArdle, J. J. (1992). A practical and theoretical guide to measurement invariance in aging research. Experimental Aging Research, 18, 117–144. https://doi.org/10.1080/03610739208253916
- Jöreskog, K. G. (1971). Statistical analysis of sets of congeneric tests. Psychometrika, 36, 109–133. https://doi.org/10.1007/BF02291393
- Kishton, J. M., & Widaman, K. F. (1994). Unidimensional versus domain representative parceling of questionnaire items: An empirical example. Educational and Psychological Measurement, 54, 757–765. https://doi.org/10.1177/0013164494054003022
- Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
- Landis, R. S., Beal, D. J., & Tesluk, P. E. (2000). A comparison of approaches to forming composite measures in structural equation models. Organizational Research Methods, 3, 186–207. https://doi.org/10.1177/109442810032003
- Lee, J., & Kim, S.-Y. (2016). Item parceling: Understanding and applying the principles. Korean Journal of Psychology: General, 35, 327–353. https://doi.org/10.22257/kjp.2016.06.35.2.327
- Little, T. D. (1997). Mean and covariance structures (macs) analyses of cross-cultural data: Practical and theoretical issues. Multivariate Behavioral Research, 32, 53–76. https://doi.org/10.1207/s15327906mbr3201_3
- 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, 9, 151–173. https://doi.org/10.1207/S15328007SEM0902_1
- Little, T. D., Rhemtulla, M., Gibson, K., & Schoemann, A. M. (2013). Why the items versus parcels controversy needn’t be one. Psychological Methods, 18, 285–300. https://doi.org/10.1037/a0033266
- 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, 181–220. https://doi.org/10.1207/s15327906mbr3302_1
- Marsh, H. W., Hey, J., Roche, L. A., & Perry, C. (1997). Structure of physical self-concept: Elite athletes and physical education students. Journal of Educational Psychology, 89, 369. https://doi.org/10.1037/0022-0663.89.2.369
- Marsh, H. W., Lüdtke, O., Nagengast, B., Morin, A. J., & Von Davier, M. (2013). Why item parcels are (almost) never appropriate: Two wrongs do not make a right—camouflaging misspecification with item parcels in CFA models. Psychological Methods, 18, 257–284. https://doi.org/10.1037/a0032773
- Marsh, H. W., Muthén, B., Asparouhov, T., Lüdtke, O., Robitzsch, A., Morin, A. J., & Trautwein, U. (2009). Exploratory structural equation modeling, integrating CFA and EFA: Application to students’ evaluations of university teaching. Structural Equation Modeling, 16, 439–476. https://doi.org/10.1080/10705510903008220
- Matsunaga, M. (2008). Item parceling in structural equation modeling: A primer. Communication Methods and Measures, 2, 260–293. https://doi.org/10.1080/19312450802458935
- McArdle, J. J. (1988). Dynamic but structural equation modeling of repeated measures data. In J. R. Nesselroade & R. B. Cattell (Eds.), Handbook of multivariate experimental psychology. Perspectives on individual differences (561–614). Boston, MA: Springer. https://doi.org/10.1007/978-1-4613-0893-5_17
- McDonald, R. P. (1989). An index of goodness-of-fit based on noncentrality. Journal of Classification, 6, 97–103.
- Meade, A. W., Johnson, E. C., & Braddy, P. W. (2008). Power and sensitivity of alternative fit indices in tests of measurement invariance. Journal of Applied Psychology, 93, 568–592. https://doi.org/10.1037/0021-9010.93.3.568
- Meade, A. W., & Kroustalis, C. M. (2006). Problems with item parceling for confirmatory factor analytic tests of measurement invariance. Organizational Research Methods, 9, 369–403. https://doi.org/10.1177/1094428105283384
- Meredith, W. (1993). Measurement invariance, factor analysis and factorial invariance. Psychometrika, 58, 525–543. https://doi.org/10.1007/BF02294825
- Meredith, W., & Teresi, J. A. (2006). An essay on measurement and factorial invariance. Medical Care, 44, 69–77. https://doi.org/10.1097/01.mlr.0000245438.73837.89
- Millsap, R. E. (2011). Statistical approaches to measurement invariance. Routledge. https://doi-org.ezproxy.lib.utexas.edu/10.4324/9780203821961
- 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, 729–757.
- Nasser-Abu Alhija, F., & Wisenbaker, J. (2006). A monte carlo study investigating the impact of item parceling strategies on parameter estimates and their standard errors in cfa. Structural Equation Modeling, 13, 204–228. https://doi.org/10.1207/s15328007sem1302_3
- Plummer, B. A. (2000). To parcel or not to parcel: The effects of item parceling in confirmatory factor analysis. https://doi.org/10.23860/diss-plummer-brett–2000
- R Core Team. (2017). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/
- Rhemtulla, M. (2016). Population performance of sem parceling strategies under measurement and structural model misspecification. Psychological Methods, 21, 348–368. https://doi.org/10.1037/met0000072
- Rioux, C., Stickley, Z. L., Odejimi, O. A., & Little, T. D. (2020). Item parcels as indicators: Why, when, and how to use them in small sample research. In R. van de Schoot & M. Miočević (Eds.), Small sample size solutions (p. 203–214).
- Rogers, W. M., & Schmitt, N. (2004). Parameter recovery and model fit using multidimensional composites: A comparison of four empirical parceling algorithms. Multivariate Behavioral Research, 39, 379–412. https://doi.org/10.1207/S15327906MBR3903_1
- Rubin, D. B. (2004). Multiple imputation for nonresponse in surveys (Vol. 81). John Wiley & Sons.
- Rushton, J. P., Brainerd, C. J., & Pressley, M. (1983). Behavioral development and construct validity: The principle of aggregation. Psychological Bulletin, 94 , 18. https://doi.org/10.1037/0033-2909.94.1.18
- Schmitt, N., & Kuljanin, G. (2008). Measurement invariance: Review of practice and implications. Human Resource Management Review, 18, 210–222. https://doi.org/10.1016/j.hrmr.2008.03.003
- Shah, R., & Goldstein, S. M. (2006). Use of structural equation modeling in operations management research: Looking back and forward. Journal of Operations Management, 24, 148–169. https://doi.org/10.1016/j.jom.2005.05.001
- Steenkamp, J.-B. E., & Baumgartner, H. (1998). Assessing measurement invariance in cross-national consumer research. Journal of Consumer Research, 25, 78–90. https://doi.org/10.1086/209528
- Steiger, J. H. (1989). Ezpath: Causal modeling: A supplementary module for systat and sygraph: Pc-ms-dos, version 1.0. Systat.
- Sterba, S. K. (2011). Implications of parcel-allocation variability for comparing fit of item-solutions and parcel-solutions. Structural Equation Modeling, 18, 554–577. https://doi.org/10.1080/10705511.2011.607073
- Sterba, S. K. (2019). Problems with rationales for parceling that fail to consider parcel-allocation variability. Multivariate Behavioral Research, 54, 264–287. https://doi.org/10.1080/00273171.2018.1522497
- Sterba, S. K., & MacCallum, R. C. (2010). Variability in parameter estimates and model fit across repeated allocations of items to parcels. Multivariate Behavioral Research, 45, 322–358. https://doi.org/10.1080/00273171003680302
- Sterba, S. K., & Rights, J. D. (2016). Accounting for parcel-allocation variability in practice: Combining sources of uncertainty and choosing the number of allocations. Multivariate Behavioral Research, 51, 296–313. https://doi.org/10.1080/00273171.2016.1144502
- Sterba, S. K., & Rights, J. D. (2017). Effects of parceling on model selection: Parcel-allocation variability in model ranking. Psychological Methods, 22, 47–68. https://doi.org/10.1037/met0000067
- 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, 4–70. https://doi.org/10.1177/109442810031002
- Wang, D., Whittaker, T. A., & Beretvas, S. N. (2012). The impact of violating factor scaling method assumptions on latent mean difference testing in structured means models. Journal of Modern Applied Statistical Methods, 11, 3. https://doi.org/10.22237/jmasm/1335844920
- Wang, J., & Wang, X. (2019). Structural equation modeling. John Wiley & Sons.
- Whittaker, T. A. (2013). The impact of noninvariant intercepts in latent means models. Structural Equation Modeling, 20, 108–130. https://doi.org/10.1080/10705511.2013.742397
- Widaman, K. F., & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. Windle, & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (p. 281–324). American Psychological Association.
- Williams, L. J., & O’Boyle, E. H., Jr. (2008). Measurement models for linking latent variables and indicators: A review of human resource management research using parcels. Human Resource Management Review, 18, 233–242 https://doi.org/10.1016/j.hrmr.2008.07.002