Analyzing multiple outcomes in clinical research using multivariate multilevel models

Journal of Consulting and Clinical Psychology

Volumn 82, Issue 5, 2014, Pages 920-930

  Baldwin, Scott A ^a   Imel, Zac E ^b   Braithwaite, Scott R ^a   Atkins, David C ^c  

^a BRIGHAM YOUNG UNIVERSITY   (United States)

^b UNIVERSITY OF UTAH   (United States)

^c UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Intervention data; Multilevel; Multivariate

Indexed keywords

ACCEPTANCE AND COMMITMENT THERAPY; ARTICLE; CLINICAL RESEARCH; COGNITIVE THERAPY; DEPRESSION; FOLLOW UP; INTERVENTION STUDY; MULTIVARIATE ANALYSIS; OUTCOME ASSESSMENT; POSTTRAUMATIC STRESS DISORDER; PSYCHOTHERAPY; QUALITY OF LIFE; HUMAN; MALE; MULTILEVEL ANALYSIS; PROCEDURES; STATISTICAL MODEL;

HUMANS; MALE; MODELS, STATISTICAL; MULTILEVEL ANALYSIS; MULTIVARIATE ANALYSIS; OUTCOME ASSESSMENT (HEALTH CARE); PSYCHOTHERAPY;

EID: 84925965926     PISSN: 0022006X     EISSN: 19392117     Source Type: Journal    
DOI: 10.1037/a0035628     Document Type: Article

References (45)

1. Atkins, D. C. (2005). Using multilevel models to analyze couple and family treatment data: Basic and advanced issues. Journal of Family Psychology, 19, 98-110. doi:10.1037/0893-3200.19.1.98
2. Baldwin, S. A., Bauer, D. J., Stice, E., & Rohde, P. (2011). Evaluating models for partially clustered designs. Psychological Methods, 16, 149-165. doi:10.1037/a0023464
3. Baldwin, S. A., & Fellingham, G. W. (2013). Bayesian methods for the analysis of small sample multilevel data with a complex variance structure. Psychological Methods, 18, 151-164. doi:10.1037/a0030642
4. Baldwin, S. A., & Imel, Z. E. (2013). Therapist effects: Findings and methods. In M. J. Lambert (Ed.), Bergin and Garfield's handbook of psychotherapy and behavior change (6th ed., pp. 258-297). New York, NY: Wiley.
5. Baldwin, S. A., Murray, D. M., & Shadish, W. R. (2005). Empirically supported treatments or Type I errors? Problems with the analysis of data from group-administered treatments. Journal of Consulting and Clinical Psychology, 73, 924-935. doi:10.1037/0022-006X.73.5.924
6. Bauer, D. J. (2003). Estimating multilevel linear models as structural equation models. Journal of Educational and Behavioral Statistics, 28, 135-167. doi:10.3102/10769986028002135
7. Bauer, D. J., Preacher, K. J., & Gil, K. M. (2006). Conceptualizing and testing random indirect effects and moderated mediation in multilevel models: New procedures and recommendations. Psychological Methods, 11, 142-163. doi:10.1037/1082-989X.11.2.142
8. Bauer, D. J., Sterba, S. K., & Hallfors, D. D. (2008). Evaluating groupbased interventions when control participants are ungrouped. Multivariate Behavioral Research, 43, 210-236. doi:10.1080/00273170802034810
9. Bollen, K. A., & Curran, P. J. (2006). Latent curve models: A structural equation perspective. Hoboken, NJ: Wiley.
10. Crits-Christoph, P., Baranackie, K., Kurcias, J. S., Beck, A. T., Carroll, K., Perry, K.,⋯ Zitrin, C. (1991). Meta-analysis of therapist effects in psychotherapy outcome studies. Psychotherapy Research, 1, 81-91. doi:10.1080/10503309112331335511
11. Crits-Christoph, P., & Mintz, J. (1991). Implications of therapist effects for the design and analysis of comparative studies of psychotherapies. Journal of Consulting and Clinical Psychology, 59, 20-26. doi:10.1037/0022-006X.59.1.20
12. Curran, P. J. (2003). Have multilevel models been structural equation models all along? Multivariate Behavioral Research, 38, 529-569. doi:10.1207/s15327906mbr3804-5
13. Fieuws, S., & Verbeke, G. (2004). Joint modelling of multivariate longitudinal profiles: Pitfalls of the random-effects approach. Statistics in Medicine, 23, 3093-3104. doi:10.1002/sim.1885
14. Gelman, A., & Hill, J. (2007). Data analysis using regression and multilevel/hierarchical models. New York, NY: Cambridge University Press.
15. Hadfield, J. D. (2010). MCMC methods for multiresponse generalized linear mixed models: The MCMCglmm R package. Journal of Statistical Software, 33, 1-22.
16. Hertzog, C., Lindenberger, U., Ghisletta, P., & van Oertzen, T. (2006). On the power of multivariate latent growth curve models to detect correlated change. Psychological Methods, 11, 244-252. doi:10.1037/1082-989X.11.3.244
17. Hofmann, S. G., & Lohr, J. M. (2010). To kill a dodo bird. The Behavior Therapist, 33, 14-15.
18. Hox, J. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York, NY: Routledge.
19. Imel, Z. E., Baldwin, S. A., Bonus, K., & Maccoon, D. (2008). Beyond the individual: Group effects in mindfulness-based stress reduction. Psychotherapy Research, 18, 735-742. doi:10.1080/10503300802326038
20. Imel, Z. E., Hubbard, R. A., Rutter, C. M., & Simon, G. (2013). Patientrated alliance as a measure of therapist performance in two clinical settings. Journal of Consulting and Clinical Psychology, 81, 154-165. doi:10.1037/a0030903
21. Jouriles, E. N., McDonald, R., Rosenfield, D., Stephens, N., Corbitt-Shindler, D., & Miller, P. C. (2009). Reducing conduct problems among children exposed to intimate partner violence: A randomized clinical trial examining effects of project support. Journal of Consulting and Clinical Psychology, 77, 705-717. doi:10.1037/a0015994
22. Kaysen, D., Atkins, D. C., Moore, S. A., Lindgren, K. P., Dillworth, T., & Simpson, T. (2011). Alcohol use, problems, and the course of posttraumatic stress disorder: A prospective study of female crime victims. Journal of Dual Diagnosis, 7, 262-279. doi:10.1080/15504263.2011.620449
23. Kenny, D. A. (1994). Interpersonal perception: A social relations analysis. New York, NY: Guilford Press.
24. Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Analysis of dyadic data. New York, NY: Guilford Press.
25. MacCallum, R. C., Kim, C., Malarkey, W. B., & Kiecolt-Glaser, J. K. (1997). Studying multivariate change using multilevel models and latent curve models. Multivariate Behavioral Research, 32, 215-253. doi: 10.1207/s15327906mbr3203-1
26. Marcus, D. K., Kashy, D. A., & Baldwin, S. A. (2009). Studying psychotherapy using the one-with-many design: The therapeutic alliance as an exemplar. Journal of Counseling Psychology, 56, 537-548. doi:10.1037/a0017291
27. Marcus, D. K., Kashy, D. A., Wintersteen, M. B., & Diamond, G. S. (2011). The therapeutic alliance in adolescent substance abuse treatment: A one-with-many analysis. Journal of Counseling Psychology, 58, 449-455. doi:10.1037/a0023196
28. McDonagh, A., Friedman, M., McHugo, G., Ford, J., Sengupta, A., Mueser, K.,⋯ Descamps, M. (2005). Randomized trial of cognitivebehavioral therapy for chronic posttraumatic stress disorder in adult female survivors of childhood sexual abuse. Journal of Consulting and Clinical Psychology, 73, 515-524. doi:10.1037/0022-006X.73.3.515
29. Mehta, P. D., & Neale, M. C. (2005). People are variables too: Multilevel structural equations modeling. Psychological Methods, 10, 259-284. doi:10.1037/1082-989X.10.3.259
30. Muthén, L. K., & Muthén, B. O. (2012). Mplus user's guide (7th ed.). Los Angeles, CA: Muthén & Muthén.
31. Nieuwenhuis, S., Forstmann, B. U., & Wagenmakers, E.-J. (2011). Erroneous analyses of interactions in neuroscience: A problem of significance. Nature Neuroscience, 14, 1105-1107. doi:10.1038/nn.2886
32. R: A Language and Environment for Statistical Computing [Computer software]. (2013). Retrieved from http://www.R-project.org/
33. Rabe-Hesketh, S., & Skrondal, A. (2008). Multilevel and longitudinal modeling using Stata. College Station, TX: Stata Press.
34. Rabe-Hesketh, S., Skrondal, A., & Pickles, A. (2002). Reliable estimation of generalized linear mixed models using adaptive quadrature. The Stata Journal, 2, 1-21.
35. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. Thousand Oaks, CA: Springer.
36. Riley, R. D., Abrams, K. R., Sutton, A. J., Lambert, P. C., & Thompson, J. R. (2007). Bivariate random-effects meta-analysis and the estimation of between-study correlation. BMC Medical Research Methodology, 7, 3. doi:10.1186/1471-2288-7-3
37. Saxon, D., & Barkham, M. (2012). Patterns of therapist variability: Therapist effects and the contribution of patient severity and risk. Journal of Consulting and Clinical Psychology, 80, 535-546. doi:10.1037/a0028898
38. Singer, J. D., & Willet, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurence. doi:10.1093/acprof:oso/9780195152968.001.0001
39. Skrondal, A., & Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal, and structural equation models. doi: 10.1201/9780203489437
40. Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling (2nd ed.). Thousand Oaks, CA: Sage.
41. Stata (Release 13) [Computer software]. (2013). College Station, TX: StataCorp.
42. Suvak, M. K., Walling, S. M., Iverson, K. M., Taft, C. T., & Resic, P. A. (2009). Multilevel regression analyses to investigate the relationship between two variables over time: Examining the longitudinal association between intrusion and avoidance. Journal of Traumatic Stress, 22, 622-631. doi:10.1002/jts.20476
43. Wampold, B. E., & Serlin, R. C. (2000). The consequences of ignoring a nested factor on measures of effect size in analysis of variance. Psychological Methods, 5, 425-433. doi:10.1037/1082-989X.5.4.425
44. White, I. R. (2011). Multivariate random-effects meta-regression: Updates to mvmeta. The Stata Journal, 11, 255-270.
45. Zheng, X., & Rabe-Hesketh, S. (2007). Estimating parameters of dichotomous and ordinal item response models with gllamm. The Stata Journal, 7, 313-333.