Multilevel modeling of a clustered continuous outcome: Nurses' work hours and burnout

Nursing Research

Volumn 54, Issue 6, 2005, Pages 406-413

  Park, Sunhee ^a   Lake, Eileen T ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Clustered data; Hierarchical structure; Multilevel models

Indexed keywords

ARTICLE; BURNOUT; CLUSTER ANALYSIS; HUMAN; METHODOLOGY; NURSING ADMINISTRATION RESEARCH; NURSING STAFF; ORGANIZATION AND MANAGEMENT; PERSONNEL MANAGEMENT; PSYCHOLOGICAL ASPECT; STATISTICAL MODEL; STATISTICS;

BURNOUT, PROFESSIONAL; CLUSTER ANALYSIS; HUMANS; LINEAR MODELS; MODELS, STATISTICAL; NURSING ADMINISTRATION RESEARCH; NURSING STAFF, HOSPITAL; PERSONNEL STAFFING AND SCHEDULING;

EID: 33644824731     PISSN: 00296562     EISSN: None     Source Type: Journal    
DOI: 10.1097/00006199-200511000-00007     Document Type: Review

References (27)

1. Aiken, L. H., Clarke, S. P., & Sloane, D. M. (2002). Hospital staffing, organization, and quality of care: Cross-national findings. International Journal for Quality in Health Care, 14(1), 5-13.
2. Allison, P. D. (1999a). Multiple regression: A primer. Thousand Oaks, CA: Pine Forge Press.
3. Allison, P. D. (1999b). Logistic regression using the SAS system: Theory and application. Gary, NC. SAS Institute.
4. Cho, S. H. (2003). Using multilevel analysis in patient and organizational outcomes research. Nursing Research, 52(1), 61-65.
5. Cho, S. H., Ketefian, S., Barkauskas, V. H., & Smith, D. G. (2003). The effects of nurse staffing on adverse events, morbidity, mortality, and medical costs. Nursing Research, 52(2), 71-79.
6. Forbes, S., & Taunton, R. L. (1994). Reliability of aggregated organizational data: An evaluation of five empirical indices. Journal of Nursing Measurement, 2(1), 37-48.
7. Guo, G., & Zhao, H. (2000). Multilevel modeling for binary data. Annual Review of Sociology, 26, 441-462.
8. Healy, M. (2001). Multilevel data and their analysis. In A. H., Leyland & H. Goldstein (Eds.), Multilevel modeling of health statistics (pp. 1-12). West Sussex: Wiley.
9. Hox, J. (2002). Multilevel analysis: Techniques and applications. Mahwah, NJ: Lawrence Erlbaum.
10. Hox, J. J., & Kreft, I. G. (1994). Multilevel analysis methods. Sociological Methods Research, 22(3), 283-299.
11. Hughes, L. C., & Anderson, R. A. (1994). Issues regarding aggregation of data in nursing systems research. Journal of Nursing Measurement, 2(1), 79-101.
12. James, L. R. (1982). Aggregation bias in estimates of perceptual agreement. Journal of Applied Psychology, 67, 219-229.
13. Kreft, I., fie De Leeuw, J. (1998). Introducing multilevel modeling. Thousand Oaks, CA: Sage.
14. Mark, B. A., Salyer, J., & Wan, T. T. (2000). Market, hospital, and nursing unit characteristics as predictors of nursing unit skill mix: A contextual analysis, Journal of Nursing Administration, 30(11), 552-560.
15. Mark, B. A., Salyer, J., & Wan, T. T. H. (2003). Professional nursing practice: Impact on organizational and patient outcomes. Journal of Nursing Administration, 33(4), 224-234.
16. Mark, B. A., Harless, D. W., McCue, M., & Xu, Y. (2004). A longitudinal examination of hospital registered nurse staffing and qualify of care. Health Services Research, 39(2), 279-300.
17. Maslach, C., Jackson, S. E., & Leiter, M. P. (1996). Maslach burnout inventory manual (3rd ed.). Palo Alto, CA: Consulting Psychologists Press.
18. McGillis Hall, L. M., Doran, D., Baker, G. R., Pink, G. H., Sidani, S., O'Brien-Pallas, L., et al. (2003). Nurse staffing models as predictors of patient outcomes. Medical Care, 41(9), 1096-1109.
19. Moore, D. S., & McCabe, G. P. (2003). Introduction to the practice of statistics (4th ed.). New York: Freeman & Co.
20. Rabe-Hesketh, S., Pickles, A., & Skrondal, A. (2001). GLLAMM manual: Technical report 2001/01. Retrieved December 27, 2003, from http.//www.gllamm. org/manual.pdf.
21. Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.
22. Raudenbush S. W., & Sampson R. J. (1999). Assessing direct and indirect effects in multilevel designs with latent variables. Sociological Methods, 28(2), 123-153.
23. Reise, S. P., & Duan, N. (1999). Multilevel modeling and its application in counseling psychology research. The Counseling Psychologist, 27(4), 528-551.
24. Teachman, J., & Crowder, K. (2002). Multilevel models in family research: some conceptual and methodological issues. Journal of Marriage and Family, 64, 280-294.
25. Wolfinger, R. D. (n.d.). Fitting nonlinear mixed models with the new NLMIXED procedure. Retrieved October 10, 2004, from http://support.sas.com/rnd/ app/papers/nlmixedsugi.pdf.
26. Wong, G. Y., & Mason, W. M. (1985). The hierarchical logistic regression model for multilevel analysis. Journal of the American Statistical Association, 80(391), 513-524.
27. Wu, Y. W. (1995). Hierarchical linear models: A multilevel data analysis technique. Nursing Research, 44(2), 123-126.