Item Parceling: Understanding and Applying the Principles

& (2016). Item Parceling: Understanding and Applying the Principles. Korean Journal of Psychology: General, 35(2), 327-353, https://doi.org/10.22257/kjp.2016.06.35.2.327

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Abstract

Item parcels, defined as the sum or mean scores of individual item scores, have been widely used in covariance structure models, such as structural equation models, because of their statistical advantages. The aims of the present study are to integrate studies on item parceling in the past 20 years and to propose appropriate methodological strategies with which researchers can apply when utilizing item parceling technology. This study first outlines the reasons why item parcels are used in light of psychometric properties and a structural equation model, and then it discusses controversies surrounding item parceling. After explaining and comparing the strategies for creating parcels, the study gives some appropriate suggestions. Finally, the study proposes steps researchers can follow and emphasizes precautions that should be considered. This study highlights the fact that using parcels is not a technique employed to resolve any problems in a model, but is a useful method to enhance the quality of research if it is used in an appropriate manner. The present study is expected to contribute to the field where item parcels are used and to enhance the quality of quantitative research.

keywords: 문항묶음, 묶음화, 구조방정식 모형, 측정모형, item parcels, parceling, structural equation modeling, measurement model

Reference

우종필 (2015). 구조방정식모델에서 다차원성개념의 항목묶음 편향에 대한 연구. 경영학연구, 44(4), 1131-1147.

조현철, 강석후 (2007). 구조방정식 모텔에서항목묶음이 인과 모수의 검정과 적합도평가에 미치는 영향. Journal of GlobalAcademy of Marketing, 17(3), 133-153.

Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.

Bagozzi, R. P., & Edwards, J. R. (1998). A general approach for representing constructs in organizational research. Organizational Research Methods, 1(1), 45-87.

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(1), 78-102.

Bandalos, D. L. (2008). Is parceling really necessary? A comparison of results from item parceling and categorical variable methodology. Structural Equation Modeling, 15(2), 211-240.

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). Mahwah, NJ: LEA.

Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.

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(3), 456-466.

10.

Cattell, R. B. (1956). Second-order personality factors in the questionnaire realm. Journal of Consulting Psychology, 20(6), 411-418.

11.

Cattell, R. B., & Burdsal Jr, C. A. (1975). The radial parcel double factoring design: A solution to the item-vs-parcel controversy. Multivariate Behavioral Research, 10(2), 165-179.

12.

Coffman, D. L., & MacCallum, R. C. (2005). Using parcels to convert path analysis models into latent variable models. Multivariate Behavioral Research, 40(2), 235-259.

13.

Cohen, P., Cohen, J., Teresi, J., Marchi, M., & Velez, C. N. (1990). Problems in the measurement of latent variables in structural equations causal models. Applied Psychological Measurement, 14, 183-196.

14.

Cook, L. L., Dorans, N. J., & Eignor, D. R. (1988). An assessment of the dimensionality of three SAT-verbal test editions. Journal of Educational and Behavioral Statistics, 13(1), 19-43.

15.

Curran, P. J., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1(1), 16–29.

16.

Gardner, H., & Hatch, T. (1989). Educational implications of the theory of multiple intelligences. Educational Researcher, 18(8), 4-10.

17.

Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25, 186-192.

18.

Guilford, J. P. (1972). Thurstone's primary mental abilities and structure-of-intellect abilities. Psychological Bulletin, 77(2), 129-143.

19.

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(2), 168-193.

20.

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(3), 233-256.

21.

Hattie, J. (1985). Methodology review: assessing unidimensionality of tests and ltenls. Applied Psychological Measurement, 9(2), 139-164.

22.

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(2), 327-351.

23.

Kenny, D. A. (1979). Correlational and causality. New York: Wiley.

24.

Kim, S. (2000). Assessment of item parcels in representing latent variables. Unpublished Doctoral Dissertation, University of Georgia, Athens.

25.

Kim, S., & Hagtvet, K. A. (2003). The impact of misspecified item parceling on representing latent variables in covariance structure modeling: A simulation study. Structural Equation Modeling, 10(1), 101-127.

26.

Kishton, J. M., & Widaman, K. F. (1994). Unidimensional versus domain representative parceling of questionnaire items: An empirical example. Educational and Psychological Measurement, 54(3), 757-765.

27.

Kline, R. B. (2011). Principles and practice of structural equation modeling. New York, NY: Guilford.

28.

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(2), 186-207.

29.

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(2), 151-173.

30.

Little, T. D., Lindenberger, U., & Nesselroade, J. R. (1999). On selecting indicators for multivariate measurement and modeling with latent variables: When “good" indicators are bad and “bad" indicators are good. Psychological Methods, 4(2), 192-211.

31.

Little, T. D., Rhemtulla, M., Gibson, K., & Schoemann, A. M. (2013). Why the items versus parcels controversy needn’t be one. Psychological Methods, 18(3), 285-300.

32.

MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4(1), 84-99.

33.

Marsh, H. W., Hau, K., 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.

34.

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(3), 257-284.

35.

Matsunaga, M. (2008). Item parceling in structural equation modeling: A primer. Communication Methods and Measures, 2(4), 260-293.

36.

Meade, A. W., & Kroustalis, C. M. (2006). Problems with item parceling for confirmatory factor analytic tests of measurement invariance. Organizational Research Methods, 9(3), 369-403.

37.

Millsap, R. E., & Kwok, O. M. (2004). Evaluating the impact of partial factorial invariance on selection in two populations. Psychological methods, 9(1), 93-115.

38.

Muthén, B. (1989). Multiple-group structural modeling with non-normal continuous variables. British Jouranl of Mathematical and Statistical Psychology, 42, 55-62.

39.

Muthén, B., & Kaplan, D. (1992). A comparison of some methodologies for the factor analysis of non‐normal likert variables: A note on the size of the model. British Journal of Mathematical and Statistical Psychology, 45(1), 19-30.

40.

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.

41.

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(2), 204-228.

42.

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(3), 379-412.

43.

Rushton, J. P., Brainered, C. J., & Pressley, M. (1983). Behavioral development and construct validity: The principle of aggregation. Psychological Bulletin, 94(1), 18-38.

44.

Samejima, F. (1970). Estimation of latent ability using a response pattern of graded scores. Psychometrika, 35(1), 139-139.

45.

Spearman, C. (1927). The abilities of man. Oxford, England: Macmillan. [Abstracts]

46.

Steenkamp, J. B. E., & Baumgartner, H. (1998). Assessing measurement invariance in cross-national consumer research. Journal of Consumer Research, 25(1), 78-107.

47.

Stephenson, M. T., & Holbert, R. L. (2003). A Monte Carlo simulation of observable versus latent variable structural equation modeling techniques. Communication Research, 30(3), 332-354.

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Article Contents

Vol.35 No.2

Item Parceling: Understanding and Applying the Principles

Abstract

Reference

Korean Journal of Psychology: General