Key driver analyses: Current trends, problems, and alternative approaches

Handbook of Employee Engagement: Perspectives, Issues, Research and Practice

Volumn , Issue , 2010, Pages 182-196

  Scherbaum, Charles A ^a   Putka, Dan J ^b   Naidoo, Loren J ^a   Youssefnia, David ^c  

^a CITY UNIVERSITY OF NEW YORK   (United States)

^b HUMAN RESOURCES RESEARCH ORGANIZATION   (United States)

^c Critical Metrics   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84881862561     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (21)

1. Anderson, D.R. (2008), Model Based Inference in the Life Sciences: A Primer on Evidence, New York: Springer Science + Business Media.
2. Azen, R., Budescu, D.V. & Reiser, B. (2001), "Criticality of predictors in multiple regression", British Journal of Mathematical and Statistical Psychology, 54, 201-25.
3. Berry, W.D. (1993), Understanding Regression Assumptions, Newbury Park, CA: Sage.
4. Budescu, D.V. (1993), "Dominance analysis: a new approach to the problem of relative importance of predictors in multiple regression", Psychological Bulletin, 114, 542-51.
5. Burnham, K.P. & Anderson, D.R. (2002), Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach, 2nd edn, New York: Springer Science + Business Media.
6. Chatfield, C. (1995), "Model uncertainty, data mining, and statistical inference", Journal of the Royal Statistical Society A, 158, 419-66.
7. Fox, J. (1991), Regression Diagnostics, Newbury Park, CA: Sage.
8. Harrell, Jr., F.E. (2001), Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis, New York: Springer Science + Business Media.
9. Hastie, T., Tibshirani, R. & Friedman, J. (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction, New York: Springer Science + Business Media.
10. Hoeting, J.A., Madigan, D., Raferty, A.E. & Volinksy, C.T. (1999), "Bayesian model averaging: a tutorial", Statistical Science, 14, 382-417.
11. James, L.R. (1980), "The unmeasured variables problem in path analysis", Journal of Applied Psychology, 65, 415-21.
12. Johnson, J.W. (2000), "A heuristic method for estimating the relative weight of predictor variables in multiple regression", Multivariate Behavioral Research, 35, 1-19.
13. Johnson, J.W. & LeBreton, J.M. (2004), "History and use of relative importance indices in organizational research", Organizational Research Methods, 7, 238-57.
14. Kelley, K. & Maxwell, S.E. (2003), "Sample size for multiple regression: obtaining regression coefficients that are accurate, not simply significant", Psychological Methods, 8, 305-21.
15. LeBreton, J.M., Binning, J.F., Adorno, A.J. & Melcher, K.M. (2004a), "Importance of personality and job-specific affect for predicting job attitudes and withdrawal behavior", Organizational Research Methods, 7, 300-325.
16. LeBreton, J.M., Hargis, M.B., Griepentrog, B., Oswald, F.L. & Ployhart, R.E. (2007), "A multidimensional approach for evaluating variables in organizational research and practice", Personnel Psychology, 60, 475-98.
17. LeBreton, J.M., Ployhart, R.E. & Ladd, R.T. (2004b), "A Monte Carlo comparison of relative importance methodologies", Organizational Research Methods, 7, 258-82.
18. Lundby, K. & Johnson, J. (2006), "Relative weights of predictors", in A. Kraut (ed.), Getting Action from Organizational Surveys, San Francisco, CA: Jossey-Bass, pp. 326-51.
19. Macey, W., Schneider, B., Barbera, K. & Young, S. (2009), Employee Engagement: Tools for Analysis, Practice, and Competitive Advantage, Malden, MA: Wiley-Blackwell.
20. Thompson, B. (1995), "Stepwise regression and stepwise discriminant analysis need not apply here: a guidelines editorial", Educational and Psychological Measurement, 55, 525-34.
21. Tonidandel, S., LeBreton, J. & Johnson, J. (2007), "Determining the statistical significance of relative weights", paper presented at the annual conference of the Society for Industrial and Organizational Psychology, New York, April.