Structural Equation Modeling Reporting Practices for Language Assessment

REFERENCES

• Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52(3), 317–332. doi:10.1007/BF02294359
   Web of Science ®Google Scholar
• Allison, P. D. (2003). Missing data techniques for structural equation modeling. Journal of Abnormal Psychology, 112(4), 545–557. doi:10.1037/0021-843X.112.4.545
   PubMed Web of Science ®Google Scholar
• Arbuckle, J. L. (2006). Amos (version 7.0) [computer program]. Chicago, IL: SPSS.
   Google Scholar
• Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. doi:10.1037/0033-2909.107.2.238
   PubMed Web of Science ®Google Scholar
• Bentler, P. M. (1995). EQS structural equations program manual. Encino, CA: Multivariate Software.
   Google Scholar
• Bentler, P. M. (2008). EQS program manual. Encino, CA: Multivariate Software, Inc.
   Google Scholar
• Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. doi:10.1037/0033-2909.88.3.588
   Web of Science ®Google Scholar
• Bentler, P. M., & Yuan, K. (2000). On adding a mean structure to a covariance structure model. Educational and Psychological Measurement, 60(3), 326–339. doi:10.1177/00131640021970574
   Web of Science ®Google Scholar
• Bollen, K. A. (1989a). A new incremental fit index for general structural equation models. Sociological Methods & Research, 17(3), 303–316. doi:10.1177/0049124189017003004
   Web of Science ®Google Scholar
• Bollen, K. A. (1989b). Structural equations with latent variables. New York, NY: John Wiley & Sons, Inc.
   Google Scholar
• Boomsma, A. (2000). Reporting analyses of covariance structures. Structural Equation Modeling: A Multidisciplinary Journal, 7(3), 461–483. doi:10.1207/S15328007SEM0703_6
   Web of Science ®Google Scholar
• Bozdogan, H. (1987). Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions. Psychometrika, 52(3), 345–370. doi:10.1007/BF02294361
   Web of Science ®Google Scholar
• Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York, NY: Guilford.
   Google Scholar
• Browne, M. W. (1984). Asymptotically distribution-free methods for the analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 37(1), 62–83. doi:10.1111/bmsp.1984.37.issue-1
   PubMed Web of Science ®Google Scholar
• Carr, N. T. (2006). The factor structure of test task characteristics and examinee performance. Language Testing, 23(3), 269–289. doi:10.1191/0265532206lt328oa
   Google Scholar
• Cheung, G. W., & Rensvold, R. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modeling: A Multidisciplinary Journal, 9(2), 233–255. doi:10.1207/S15328007SEM0902_5
   Web of Science ®Google Scholar
• Graham, J., Guthrie, A., & Thompson, B. (2003). Consequences of not interpreting structure coefficients in published CFA research: A reminder. Structural Equation Modeling: A Multidisciplinary Journal, 10(1), 142–153. doi:10.1207/S15328007SEM1001_7
   Web of Science ®Google Scholar
• Gu, L. (2014). At the interface between language testing and second language acquisition: Language ability and context of learning. Language Testing, 31(1), 111–133. doi:10.1177/0265532212469177
   Web of Science ®Google Scholar
• Hoyle, R. H., & Isherwood, J. C. (2013). Reporting results from structural equation modeling analyses in Archives of Scientific Psychology. Archives of Scientific Psychology, 1(1), 14–22. doi:10.1037/arc0000004
   Google Scholar
• Hoyle, R. H., & Panter, A. T. (1995). Writing about structural equation models. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 158–176). Thousand Oaks, CA: Sage Publications.
   Google Scholar
• 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. doi:10.1080/10705519909540118
   Web of Science ®Google Scholar
• In’nami, Y., & Koizumi, R. (2011). Structural equation modeling in language testing and learning research: A review. Language Assessment Quarterly, 8(3), 250–276. doi:10.1080/15434303.2011.582203
   Web of Science ®Google Scholar
• In’nami, Y., & Koizumi, R. (2012). Factor structure of the revised TOEIC™ test: A multiple-sample analysis. Language Testing, 29(1), 131–152. doi:10.1177/0265532211413444
   Web of Science ®Google Scholar
• Jöreskog, K. G., & Sörbom, D. (1981). Listrel V: Analysis of linear structural relationships by the method of maximum likelihood. Chicago, IL: National Education Resources.
   Google Scholar
• Jöreskog, K. G., & Sörbom, D. (2006). Listrel 8.8 for windows [computer software]. Skokie, IL: Scientific Software International, Inc.
   Google Scholar
• Kline, R. (2011). Principles and practice of structural equation modeling (2nd ed.). New York, NY: The Guilford Press.
   Google Scholar
• Kunnan, A. J. (1994). Modelling relationships among some test-taker characteristics and performance on EFL tests: An approach to construct validation. Language Testing, 11(3), 225–250. doi:10.1177/026553229401100301
   Google Scholar
• Kunnan, A. J. (1998). An introduction to structural equation modelling for language assessment research. Language Testing, 15(3), 295–332. doi:10.1177/026553229801500302
   Google Scholar
• Lee, T., & Cai, L. (2012). Alternative multiple imputation inference for mean and covariance structure modeling. Journal of Educational and Behavioral Statistics, 37(6), 675–702. doi:10.3102/1076998612458320
   Web of Science ®Google Scholar
• Llosa, L. (2005). Building and supporting a validity argument for a standards-based classroom assessment of English proficiency. ( Unpublished PhD dissertation). University of California, Los Angeles, CA.
   Google Scholar
• Llosa, L. (2007). Validating a standards-based classroom assessment of English proficiency: A multitrait-multimethod approach. Language Testing, 24(4), 489–515. doi:10.1177/0265532207080770
   Google Scholar
• Long, J. S. (1983). Covariance structure models: An introduction to LISREL. Beverly Hills, CA: Sage.
   Google Scholar
• MacCallum, R. C. (1986). Specification searches in covariance structure modeling. Psychological Bulletin, 100(1), 107–120. doi:10.1037/0033-2909.100.1.107
   Web of Science ®Google Scholar
• Maccallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. doi:10.1037/1082-989X.1.2.130
   Web of Science ®Google Scholar
• MacCallum, R. C., Roznowski, M., & Necowitz, L. (1992). Model modifications in covariance structure analysis: The problem of capitalization on chance. Psychological Bulletin, 111(3), 490–504. doi:10.1037/0033-2909.111.3.490
   PubMed Web of Science ®Google Scholar
• MacCallum, R. C., Widaman, K. F., Zhang, S., & Hong, S. (1999). Sample size in factor analysis. Psychological Methods, 4(1), 84–99. doi:10.1037/1082-989X.4.1.84
   Web of Science ®Google Scholar
• Mardia, K. V. (1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530. doi:10.1093/biomet/57.3.519
   Web of Science ®Google Scholar
• McDonald, R., & Ho, M. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7(1), 64–82. doi:10.1037/1082-989X.7.1.64
   PubMed Web of Science ®Google Scholar
• Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.
   Google Scholar
• Ockey, G. J. (2011). Self-consciousness and assertiveness as explanatory variables of L2 oral ability: A latent variable approach. Language Learning, 61(3), 968–989. doi:10.1111/lang.2011.61.issue-3
   Web of Science ®Google Scholar
• Ockey, G. J. (2014). Exploratory factor analysis and structural equation modeling. In A. J. Kunnan (Ed.), The companion to language assessment (pp. 1224–1244). NJ: John Wiley & Sons. doi:10.1002/9781118411360.wbcla114
   Google Scholar
• Phakiti, A. (2008). Strategic competence as a fourth order factor model: A structural equation modeling approach. Language Assessment Quarterly, 5(1), 20–42. doi:10.1080/15434300701533596
   Web of Science ®Google Scholar
• Purpura, J. (1999). Strategy use and second language test performance: A structural equation modeling approach. Cambridge, UK: Cambridge University Press.
   Google Scholar
• Purpura, J. E. (1997). An analysis of the relationships between test takers’ cognitive and metacognitive strategy use and second language test performance. Language Learning, 47(2), 289–325. doi:10.1111/0023-8333.91997009
   Web of Science ®Google Scholar
• Purpura, J. E. (1998). Investigating the effects of strategy use and second language test performance with high- and low-ability test takers: A structural equation modelling approach. Language Testing, 15(3), 333–379.
   Google Scholar
• Purpura, J. E. (2004). Validating questionnaires to examine personal factors in L2 test performance. In M. Milanovich, & C. Weir (Eds.), European language testing in a global context. Proceedings of the Association of Language Testers of Europe (ALTE) conference in Barcelona (pp. 93–115). Cambridge, UK: Cambridge University Press.
   Google Scholar
• Raftery, A. E. (1995). Bayesian model selection in social research. In A. E. Raferty (Ed.), Sociological methodology (pp. 111–164). Oxford, UK: Blackwell.
   Google Scholar
• Raykov, T., & Marcoulides, G. (2006). A first course in structural equation modeling (2nd ed.). Mawah, NJ: Lawrence Erlbaum Associates.
   Google Scholar
• Raykov, T., Tomer, A., & Nesselroade, J. R. (1991). Reporting structural equation modeling results in psychology and aging: Some proposed guidelines. Psychology and Aging, 6(4), 499–503. doi:10.1037/0882-7974.6.4.499
   PubMed Web of Science ®Google Scholar
• Rubin, D. B. (1976). Inference and missing data. Biometrika, 63(3), 581–592. doi:10.1093/biomet/63.3.581
   Web of Science ®Google Scholar
• Satorra, A., & Bentler, P. M. (1988). Scaling correction for chi-square statistics in covariance structure analysis. Proceedings of the American Statistical Association, 36, 308–313.
   Google Scholar
• Satorra, A., & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye, & C. C. Clogg (Eds.), Latent variable analysis: Applications for developmental research (pp. 399–419). Thousand Oaks, CA: Sage.
   Google Scholar
• Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514. doi:10.1007/BF02296192
   Web of Science ®Google Scholar
• Satorra, A., & Bentler, P. M. (2010). Ensuring positiveness of the scaled difference chi-square test statistic. Psychometrika, 75(2), 243–248. doi:10.1007/s11336-009-9135-y
   PubMed Web of Science ®Google Scholar
• Satorra, A., & Saris, W. E. (1985). Power of the likelihood ratio test in covariance structure analysis. Psychometrika, 50(1), 83–90. doi:10.1007/BF02294150
   Web of Science ®Google Scholar
• Sawaki, Y. (2007). Construct validation of analytic rating scales in a speaking assessment: Reporting a score profile and a composite. Language Testing, 24(3), 355–390. doi:10.1177/0265532207077205
   Google Scholar
• Sawaki, Y., Stricker, L. J., & Oranje, A. H. (2009). Factor structure of the TOEFL Internet-based test. Language Testing, 26(1), 5–30. doi:10.1177/0265532208097335
   Web of Science ®Google Scholar
• Schumacker, R., & Lomax, R. (2010). A beginner’s guide to structural equation modeling (3rd ed.). Mawah, NJ: Lawrence Erlbaum Associates.
   Google Scholar
• Schwarz, G. E. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. doi:10.1214/aos/1176344136
   Web of Science ®Google Scholar
• Shin, S. (2005). Did they take the same test? Examinee language proficiency and the structure of language tests. Language Testing, 22(1), 31–57. doi:10.1191/0265532205lt296oa
   Google Scholar
• Steiger, J. H., & Lind, J. C. (1980, May). Statistically based tests for the number of common factors. Paper presented at the annual meeting of the Psychometric Society, Iowa City, IA.
   Google Scholar
• Tucker, L. R., & Lewis, C. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10. doi:10.1007/BF02291170
   Web of Science ®Google Scholar
• Ullman, J. (2001). Structural equation modeling. In B. Tabachnick, & L. Fidell (Eds.), Using multivariate statistics (4th ed., pp. 653–771). Boston, MA: Allyn and Bacon.
   Google Scholar