A validation of the factor structure of OQ-45 scores using factor mixture modeling

Measurement and Evaluation in Counseling and Development

Volumn 42, Issue 4, 2010, Pages 275-295

  Kim, Seong Hyeon ^a   Beretvas, S Natasha ^b   Sherry, Alissa R ^b  

^a FULLER THEOLOGICAL SEMINARY   (United States)

^b UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

Factor mixture modeling; Factorial validity; Outcome Questionnaire; Psychotherapy outcome measurement

Indexed keywords

EID: 73449136843     PISSN: 07481756     EISSN: 19476302     Source Type: Journal    
DOI: 10.1177/0748175609354616     Document Type: Article

References (66)

1. Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52, 317-332.
2. Allua, S., Stapleton, L.M., & Beretvas, S.N. (2008). Testing latent mean differences between observed and unobserved groups using multilevel factor mixture models. Educational and Psychological Measurement, 63 (3). 357-378.
3. American Psychological Association. (2004, October). The president signs the Garrett Lee Smith Memorial Act. Retrieved June 8, 2008, from http://www.apa.org/ppo/issues/eglsbillsign.html
4. Bauer, D.J., & Curran, P.J. (2004). The integration of continuous and discrete latent variable models: Potential problems and promising opportunities. Psychological Methods, 9, 3-29.
5. Beck, A.T., Ward, C.H., Mendelson, M., Mock, J., & Erbaugh, J. (1961). An inventory for measuring depression. Archives of General Psychology, 4, 53-56.
6. Benton, S.A., Robertson, J.M., Tseng, W. -.C., Newton, F.B., & Benton, S.L. (2003). Changes in counseling center client problems across 13 years. Professional Psychology: Research and Practice, 34, 66-72.
7. Beretvas, S.N., & Kearney, L.K. (2003). A shortened form of the Outcome Questionnaire: A validation of scores across groups (A research report of the Research Consortium of Counseling and Psychological Services for Higher Education). Austin: University of Texas at Austin, Counseling and Mental Health Center.
8. Celeux G., & Soromenho G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13, 195-212.
9. Colder, C.R., Campbell, R.T., Ruel, E., Richardson, J.L., & Flay, B.R. (2002). A finite mixture model of growth trajectories of adolescent alcohol use: Predictors and consequences. Journal of Consulting and Clinical Psychology, 70, 976-985.
10. Derogatis, L.R., & Cleary, P.A. (1977). Confirmation of the dimensional structure of the SCL-90: A study in construct validation. Journal of Clinical Psychology, 33, 981-989.
11. Derogatis, L.R., Rickels, K., & Rock, A.F. (1976). The SCL-90 and the MMPI: A step in the validation of a new self-report scale. British Journal of Psychology, 128, 280-289.
12. Ellickson, P.L., Martino, S.C., & Collins, R.L. (2004). Marijuana use from adolescence to young adulthood: Multiple developmental trajectories and their associated outcomes. Health Psychology, 23, 299-307.
13. Floyd, F.J., & Widaman, K.F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7, 286-299.
14. Gagné, P. (2006). Mean and covariance structure mixture models. In G. R. Hancock & R. D. Mueller (Eds.), Structural equation modeling: A second course (pp. 197-224). Greenwich, CT: Information Age Publishing.
15. Hair, J.F., Jr., Anderson, R.E., Tatham, R.L., & Black, W.C. (1998). Multivariate data analysis (5 th ed.). Upper Saddle River, NJ: Prentice Hall.
16. Hancock, G.R., Stapleton, L.M., & Arnold-Berkovits, I. (2006). The tenuousness of invariance tests within multisample covariance and mean structure models. Unpublished manuscript.
17. Hannan, C., Lambert, M.J., Harmon, C., Nielsen, S.L., Smart, D.W., Shimokawa, K., et al. (2005). A lab test and algorithms for identifying clients at risk for treatment failure. Journal of Clinical Psychology, 61, 155-163.
18. Hansen, N.B., Lambert, M.J., & Forman, E.M. (2002). The psychotherapy dose-response effect and its implications for treatment delivery services. Clinical Psychology: Science and Practice, 9, 329-343.
19. Hatfield, D.R., & Ogles, B.M. (2004). The use of outcome measures by psychologists in clinical practice. Professional Psychology: Research and Practice, 35, 485-491.
20. Hessen, D.J., Dolan, C.V., & Wicherts, J.M. (2006). The multigroup common factor model with minimal uniqueness constraints and the power to detect uniform bias. Applied Psychological Measurement, 30, 233-246.
21. Horowitz, L.M., Rosenberg, S.E., Baer, B.A., Ureño, G., & Vilaseñor, V.S. (1988). Inventory of interpersonal problems: Psychometric properties and clinical applications. Journal of Consulting and Clinical Psychology, 56, 885-892.
22. Hu, L.-T., & Bentler, P.M. (1999). Cutoff criteria for fit indices in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 1, 1-55.
23. Jackson, K.M., & Sher, K.J. (2005). Similarities and differences of longitudinal phenotypes across alternate indices of alcohol involvement: A methodologic comparison of trajectory approaches. Psychology of Addictive Behaviors, 19, 339-351.
24. Jacobson, N.S., & Truax, P. (1991). Clinical significance: A statistical approach to defining meaningful change in psychotherapy research. Journal of Consulting and Clinical Psychology, 59, 12-19.
25. Jedidi, K., Jagpal, H.S., & DeSarbo, W.S. (1997). Finite-mixture structural equation models for response-based segmentation and unobserved heterogeneity. Marketing Science, 16, 39-59.
26. Lambert, M.J., Burlingame, G.M., Umphress, V., Hansen, N.B., Vermeersch, D.A., Clouse, G.C., et al. (1996). The reliability and validity of the Outcome Questionnaire. Clinical Psychology and Psychotherapy, 3, 249-258.
27. Lambert, M.J., Gregersen, A.T., & Burlingame, G.M. (2004). The Outcome Questionnaire. In M. E. Maruish (Ed.), The use of psychological testing for treatment planning and outcome assessment: Vol. 3. Instruments for adults (3 rd ed., pp. 191-234). Mahwah, NJ: Lawrence Erlbaum.
28. Lambert, M.J., Hansen, N.B., & Finch, A.E. (2001). Patient-focused research: Using patient outcome data to enhance treatment effects. Journal of Consulting and Clinical Psychology, 69, 159-172.
29. Lambert, M.J., Lunnen, K., Umphress, V., Hansen, N.B., & Burlingame, G.M. (1994). Administration and scoring manual for the Outcome Questionnaire (OQ-45.1). Salt Lake City, UT: IHC Center for Behavioral Healthcare Efficacy.
30. Lambert, M.J., Whipple, J.L., Bishop, M.J., Vermeersch, D.A., Gray, G.V., & Finch, A.E. (2002). Comparison of empirically-derived and rationally-derived methods for identifying patients at risk for treatment failure. Clinical Psychology and Psychotherapy, 9, 149-164.
31. Lo, Y., Mendell, N.R., & Rubin, D.B. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 767-778.
32. Lubke, G.H., & Muthén, B.O. (2005). Investigating population heterogeneity with factor mixture models. Psychological Methods, 10, 21-39.
33. Lubke, G.H., & Muthén, B.O. (2007). Performance of factor mixture models as a function of model size, covariate effects, and class-specific parameters. Structural Equation Modeling, 14, 26-47.
34. McLachlan, G., & Peel, D. (2000). Finite mixture models. New York: Wiley.
35. Meade, A.W., Lautenschlager, G.J., & Hecht, J.E. (2005). Establishing measurement equivalence and invariance in longitudinal data with item response theory. International Journal of Testing, 5, 279-300.
36. Meredith, W. (1993). Measurement invariance, factor analysis, and factorial invariance. Pyschometrika, 58, 525-543.
37. Meredith, W., & Horn, J. (2001). The role of factorial invariance in modeling growth and change. In L. M. Collins & A. G. Sayer (Eds.), New methods for the analysis of change: Decade of behavior (pp. 203-240). Washington, DC: American Psychological Association.
38. Messick, S. (1998). Test validity: A matter of consequence. Social Indicators Research, 45, 35-44.
39. Mueller, R.M., Lambert, M.J., & Burlingame, G.M. (1998). Construct validity of the Outcome Questionnaire: A confirmatory factor analysis. Journal of Personality Assessment, 70, 248-262.
40. Muthén, B.O. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), The Sage handbook of quantitative methodology for the social sciences (pp. 345-368). Newbury Park, CA: Sage.
41. MuthÃn, B.O. (2006). Should substance use disorders be considered as categorical or dimensional ? Addiction, 101, 6-16.
42. Muthén, L.K., & Muthén, B.O. (1998-2007). Mplus userĝ€™s guide (4 th ed.). Los Angeles: Muthén & Muthén.
43. Muthén, L.K., & Muthén, B.O. (2007). Mplus (Version 5.0) [Computer Software]. Los Angeles: Muthén & Muthén.
44. Muthén, B.O., & Shedden, K. (1999). Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics, 55, 463-469.
45. Nylund, K.L., Asparouhov, T., & Muthén, B.O. (2006). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Manuscript submitted for publication.
46. Okiishi, J., Lambert, M.J., Nielsen, S.L., & Ogles, B.M. (2003). Waiting for supershrink: An empirical analysis of therapist effects. Clinical Psychology and Psychotherapy, 10, 361-373.
47. Raykov, T., & Marcoulides, G.A. (2006). A first course in structural equation modeling (2 nd ed.). Mahwah, NJ: Lawrence Erlbaum.
48. Reinecke, J. (2006). Longitudinal analysis of adolescentsĝ€ ™ deviant and delinquent behavior: Applications of latent class growth curves and growth mixture models. Methodology, 2, 100-112.
49. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6, 461-464.
50. Sclove, L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 52, 333-343.
51. Sharkin, B.S., & Coulter, L.P. (2005). Empirically supporting the increasing severity of college counseling center client problems: Why is it so challenging ? Journal of College Counseling, 8, 165-171.
52. Spielberger, C.D. (1983). Manual for the State-Trait Anxiety Inventory STAI (Form Y). Palo Alto, CA: Consulting Psychologists Press.
53. Spielberger, C., Gorsuch, A., & Lushene, R. (1970). The state-trait anxiety inventory. Palo Alto, CA: Consulting Psychologist Press.
54. Taylor, J.A. (1953). A personality scale of manifest anxiety. Journal of Abnormal and Social Psychology, 48, 285-290.
55. Tucker, J.S., Orlando, M., & Ellickson, P.L. (2003). Patterns and correlates of binge drinking trajectories from early adolescence to young adulthood. Health Psychology, 22, 79-87.
56. Umphress, V.J., Lambert, M.J., Smart, D.W., Barlow, S.H., & Clouse, G. (1997). Concurrent and construct validity of the Outcome Questionnaire. Journal of Psychoeducational Assessment, 15, 40-55.
57. Vermeersch, D.A., Lambert, M.J., & Burlingame, G.A. (2000). Outcome Questionnaire: Item sensitivity to change. Journal of Personality Assessment, 74, 242-261.
58. Vermeersch, D.A., Whipple, J.L., Lambert, M.J., Hawkins, E.J., Burchfield, C.M., & Okiishi, J.C. (2004). Outcome Questionnaire: Is it sensitive to changes in counseling center clients ? Journal of Counseling Psychology, 51, 38-49.
59. Wampold, B.E., & Brown, G.S. (2005). Estimating variability in outcomes attributable to therapists: A naturalistic study of outcomes in managed care. Journal of Consulting and Clinical Psychology, 73, 914-923.
60. Weissman, M.M., & Bothwell, S. (1976). Assessment of social-adjustment by patient self-report. Archives of General Psychiatry, 33, 1111-1115.
61. Whipple, J.L., Lambert, M.J., Vermeersch, D.A., Smart, D.W., Nielsen, S.L., & Hawkins, E.J. (2003). Improving the effects of psychotherapy: The use of early identification of treatment failure and problem-solving strategies in routine practice. Journal of Counseling Psychology, 50, 59-68.
62. White, H.R., Bates, M.E., & Buyske, S. (2001). Adolescence-limited versus persistent delinquency: Extending Moffittĝ€™s hypothesis into adulthood. Journal of Abnormal Psychology, 110, 600-609.
63. Wicherts, J.M., Dolan, C.V., & Hessen, D.J. (2005). Stereotype threat and group differences in test performance: A question of measurement invariance. Journal of Personality and Social Psychology, 89, 696-716.
64. 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 (pp. 281-324). Washington, DC: American Psychological Association.
65. Zung, W.W. (1965). A self-rating depression scale. Archives of General Psychiatry, 12, 63-70.
66. Zung, W.W. (1971). A rating instrument for anxiety disorders. Psychosomatics, 6, 371-379.