A two-facet measurement methodology for assessing item parcels: An application to measuring political knowledge in secondary school

Scandinavian Journal of Educational Research

Volumn 49, Issue 4, 2005, Pages 399-417

  Hagtvet, Knut A ^a   Solhaug, Trond ^a  

^a UNIVERSITY OF OSLO   (Norway)

Author keywords

Item parcel indicators; Two facet measurement model; Unidimensionality

Indexed keywords

EID: 27944454822     PISSN: 00313831     EISSN: None     Source Type: Journal    
DOI: 10.1080/00313830500202983     Document Type: Article

References (78)

1. Aish, A.-M., & Jøreskog, K. G. (1990). A panel model for political efficacy and responsiveness: An application of LISREL 7 with weighted least squares. Quality & Quantity, 24, 405-426.
2. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423.
3. Bagozzi, R. P., & Heatherton, T. F. (1994). A general approach to representing multifaceted personality constructs: Applications to state self-esteem. Structural Equation Modeling, 1, 35-67.
4. Bandalos, D. (1999). The effects of item parceling in structural equation modeling: A Monte Carlo study. Paper presented at the Annual Meeting of the American Educational Research Association, Montreal, Canada, April.
5. Bandalos, D., & Finney, S. (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. 269-295). Hillsdale, NJ: Erlbaum.
6. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness-of-fit in the analysis of covariance structures. Psychological Bulletin, 88, 588-606.
7. Bentler, P. M., & Chou, C. (1987). Practical issues in structural modeling. Sociological Methods and Research, 16, 78-117.
8. Bernstein, I. H., & Teng, G. (1989). Factoring items and factoring scales are different. Spurious evidence for multidimensionality due to item categorization. Psychological Bulletin, 105, 467-477.
9. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
10. Bollen, K., & Lennox, R. (1991). Conventional wisdom on measurement. A structural equation perspective. Psychological Bulletin, 110, 305-314.
11. Brennan, R. L. (1992). Elements of generalizability theory. Iowa City, IA: ACT.
12. Brennan, R. L. (2001). Generalizability theory. New York: Springer.
13. Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). Newbury Park, CA: Sage.
14. Carpini, M. X. D., & Keeter, S. (1993). Measuring political knowledge: Putting first things first. American Political Science Review, 37, 1179-1206.
15. Cattell, R. B. (1956). Validation and intensification of the sixteen personality factor questionnaire. Journal of Clinical Psychology, 12, 205-214.
16. Cattell, R. B., & Burdsal, C. A. (1975). The radical parcel double factoring design: A solution to the item-vs-parcel controversy. Multivariate Behavioral Research, 10, 165-179.
17. Cohen, P., Cohen, J., Teresi, J., Marchi, M., & Noemi Velez, C. (1990). Problems in the measurement of latent variables in structural equations causal models. Applied Psychological Measurement, 14, 183-196.
18. Colton, D. A. (2002, April). Approaching validity through testlets. Paper presented at the Annual Meeting of the National Council on Measurement in Education, New Orleans, April.
19. Cortina, J. M. (1993). What is the coefficient alpha? An examination of theory and application. Journal of Applied Psychology, 78, 98-104.
20. Cronbach, L. J., Gleser, G. C., Nanda, H., & Rajaratnam, N. (1972). The dependability of behavioral measurement. Theory of generalizability for scores and profiles. New York: Wiley.
21. DiStefano, C. A. (1998). The effects of ignoring the metric level of data in confirmatory factor analysis. Unpublished doctoral dissertation, University of Georgia, Athens, Georgia.
22. Eysenck, H. J., & Eysenck, S. B. G. (1969). Personality structure and measurement. London: Routledge & Kegan Paul.
23. Farnham-Diggory, S. (1992). Cognitive processes in education. New York: Harper Collins.
24. Green, S. B., Lissitz, R. W., & Mulaik, S. A. (1977). Limitations of coefficient alpha as an index of test unidimensionality. Educational and Psychological Measurement, 37, 827-838.
25. Gribbons, B. C., & Hocevar, D. (1998). Levels of aggregation in higher level confirmatory factor analysis: Application for academic self-concept. Structural Equation Modeling, 5, 377-390.
26. Hagtvet, K. A. (1998). Assessment of latent constructs: a joint application of generalizability theory and covariance modeling with an emphasis on inference and structure. Scandinavian Journal of Educational Research, 42, 41-63.
27. Hagtvet, K. A. (1999). A covariance modeling approach to investigate dimensionality within a generalizability framework. Paper presented at the Annual Meeting of the American Educational Research Association, Montreal, Canada, April.
28. Hagtvet, K. A., & Kim, S. (2000). Assessing unidimensionality of item parcels in structural equation modeling: A simulation study. Paper presented at the Annual Meeting of the American Educational Research Association, New Orleans, LA, April.
29. Hagtvet, K. A., Man, F., & Sharma, S. (2001). Generalizability of self-related cognitions in test anxiety. Personality and Individual Differences, 31, 1147-1171.
30. 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.
31. Hagtvet, K. A., & Zuo, L. (2000). Conceptual and empirical components of an internal domain study: An illustration in terms of the Achievement Motives Scale. Scandinavian Journal of Educational Research, 44, 49-78.
32. 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.
33. Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.
34. Jarjoura, D., & Brennan, R. L. (1983). Multivariate generalizability models for tests developed according to a table of specifications. In L. J. Fyans (Ed.), New directions for testing and measurement: Generalizability theory (pp. 83-101). San Francisco: Jossey-Bass.
35. Joormann, J., & Stöber, J. (1997). Measuring facets of worry: A Lisrel analysis of the Worry Domains questionnaire. Personality and Individual Differences, 23, 827-837.
36. Jøreskog, K. G. (1971). Simultaneous factor analysis in several populations. Psychometrika, 36, 409-426.
37. Jøreskog, K. G. (1979). Basic ideas of factor analysis and component analysis. In K. G. Jøreskog & D. Sørbom (Eds.), Advances in factor analysis and structural equation models (pp. 5-20). Cambridge, MA: Abt Books.
38. Jøreskog, K. G. (1990). New developments in LISREL: Analysis of ordinal variables using polychoric correlations and weighted least squares. Quality & Quantity, 24, 387-404.
39. Jøreskog, K. G. (1994). Testing structural equation model. In K. A. Bollen & J. Scott Long (Eds.), Testing structural equation models (pp. 294-316). Newbury Park, CA: Sage.
40. Jøreskog, K. G., & Moustaki, I. (2001). Factor analysis of ordinal variables: A comparison of three approaches. Multivariate Behavioral Research, 36, 347-387.
41. Jøreskog, K. G., & Sørbom, D. (1985). LISREL VI: Analysis of linear structural relationships by the method of maximum likelihood. Mooresville, IN: Scientific Software.
42. Jøreskog, K. G., & Sørbom, D. (1988). LISREL 7: A guide to the program and applications. Chicago: SPSS.
43. Jøreskog, K. G., & Sørbom, D. (1993). LISREL8: Structural equation modeling with the SIMPLIS command language. Chicago: Scientific Software.
44. Jøreskog, K. G., & Sørbom, D. (1996). PRELIS2: User's reference guide. Chicago: Scientific Software.
45. Jøreskog, K. G., Sørbom, D., & du Toit, S. H. C. (2000). LISREL8: New statistical features. Chicago: Scientific Software.
46. Kaplan, D. (1988). The impact of specification error on the estimation, testing and improvement of structural equation models. Multivariate Behavioral Research, 23, 69-86.
47. Kaplan, D. (1989). Model modification in covariance structure analysis: Application of the expected parameter change. Multivariate Behavioral Research, 24, 285-305.
48. Kaplan, D. (2000). Structural equation modeling. Thousand Oaks, CA: Sage.
49. Kim, S. (2000). Assessment of item parcels in representing latent variables. Unpublished doctoral dissertation, The University of Georgia, Athens, Georgia.
50. Kim, S., & Hagtvet, K. A. (2003). The impact of misspecified item parceling on representing latent variables in covariance structural modeling: A simulation study. Structural Equation Modeling, 10, 101-127.
51. 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.
52. Kirke-, utdannings, og forskningsdepartementet. (1994) Læreplan for videregående opplæring-Samfunnslære. Videregående kurs 1 felles allment fag for alle studieretninger [Curriculum for upper secondary education-Civics, advanced course 1, Common general subject for all areas of study; in Norewgian]. Oslo, Norway: Kirke-utdanningss- og forskningsdepartementet.
53. 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.
54. Lee, G., Brennan, R. L., & Friesbie, D. A. (2000). Incorporating the testlet concept in test score analyses. Educational Measurement: Issues and Practice, 19, 9-15.
55. 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.
56. MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4, 84-99.
57. 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.
58. McDonald, R. P. (1981). The dimensionality of tests and items. British Journal of Mathematical and Statistical Psychology, 34, 100-117.
59. Muthén, L. K., & Muthén, B. O. (1998). Mplus. User's guide. Los Angeles: Muthén & Muthén.
60. Nasser, F., Takahashi, T., & Benson, J. (1997). The structure of test anxiety in Israeli-Arab high school students: An application of confirmatory factor analysis with miniscales. Anxiety, Stress, and Coping, 10, 129-151.
61. Niemi, R. G., & Junn, J. (1998). Civic education. What makes students Learn? London: Yale University Press.
62. Prats, D. C. (1990). The effects of forming miniscales on the construct validity of the test anxiety inventory. Paper presented at the National Council on Measurement in Education, Boston.
63. Reuterberg, S., & Gustafsson, J. (1990). Confirmatory factor analysis and reliability: Testing measurement model assumptions. Goteborg, Sweden: University of Goteborg Department of Education and Educational Research.
64. Rushton, J. P., Brainerd, J. C., & Pressley, M. (1983). Behavioral development and construct validity: The principle of aggregation. Psychological Bulletin, 94, 18-38.
65. Saris, W. E., Satorra, A., & Sørbom, D. (1987). The detection and correction of specification errors in structural equation models. In C. C. Cloggs (Ed.), Sociological methodology (pp. 105-129). San Francisco: Jossey-Bass.
66. Satorra, A., & Bentler, P. M. (1988). Scaling corrections for chi-square statistics in covariance structure analysis. Proceedings of the Business and Economic Statistics Section of the American Statistical Association, 1988, 308-313.
67. Schau, C., Stevens, J., Dauphinee, T., & Vecchio, A. D. (1995). The development and validation of the survey of attitudes toward statistics. Educational and Psychological Measurement, 55, 868-875.
68. Skaalvik, E. M., & Hagtvet, K. A. (1990). Academic achievement and self-concept: An analysis of causal predominance in a developmental perspective. Journal of Personality and Social Psychology, 58, 292-307.
69. Sobel, M. E., & Bohrnstedt, G. W. (1985). Use of null models in evaluating the fit of covariance structure models. In N. B. Tuma (Ed.), Sociological methodology 1985 (pp. 152-178). San Francisco: Jossey-Bass.
70. Solhaug, T. (2001). On the measurement of political knowledge. Paper presented at the IPSA/RPSEA Round Table Conference on Political Socialization, Participation, and Political Education, Wuppertal, Germany, June.
71. Solhaug, T. (2003). Utdanning til demokratisk medborgerskap [Education for democratic citizenship; in Norwegian]. Unpublished doctoral dissertation, Department of Teacher Education and School Development. University of Oslo, Norway.
72. Spearman, C. (1904). General intelligence: Objectively determined and measured. American Journal of Psychology, 15, 201-293.
73. Spearman, C. (1914). The theory of two factors. Psychological Review, 21, 101-115.
74. Takahashi, T., & Nasser, F. (1996). The impact of using item parcels on ad hoc goodness of fit indices in confirmatory factor analysis: An empirical example. Paper presented at the Annual Meeting of the American Educational Research Association, New York, April.
75. Thompson, B., & Melancon, J. G. (1996). Using item "testlets" "parcels" in confirmatory factor analysis: An example using the PPSDQ-78. Paper presented at the Annual Meeting of the Mid-South Educational Research Association, Tuscaloosa, AL.
76. Thurstone, L. L. (1931). Multiple factor analysis. Psychological Review, 38, 406-427.
77. Yuan, K.-H., Bentler, P. M., & Kano, Y. (1997). On averaging variables in a CFA model. Behaviormetrika, 24, 71-83.
78. West, S. G., Finch, J. F., & Curra, P. J. (1995). Structural equation models with non-normal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling. Concepts, issues, and applications (pp. 56-75). London: Sage.