Missing data techniques and low response rates: The role of systematic nonresponse parameters

Statistical and Methodological Myths and Urban Legends: Doctrine, Verity and Fable in the Organizational and Social Sciences

Volumn , Issue , 2008, Pages 7-36

  Newman, Daniel A ^a  

^a NONE

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EID: 84909233571     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.4324/9780203867266     Document Type: Chapter

References (48)

1. Aguinis, H., Beaty, J. C., Boik, R. J., & Pierce, C. A. (2005). Effect size and power in assessing moderating effects of categorical variables using multiple regression: A 30-year review. Journal of Applied Psychology, 90, 94-107.
2. Ajzen, I. (1988). Attitudes, personality, and behavior. Homewood, IL:Dorsey Press.
3. Borgatti, S. P., Carley, K. M., & Krackhardt D. (2006). On the robustness of centrality measures under conditions of imperfect data. Social Networks, 28, 124-136.
4. Burt, R. S. (1987). A note on missing network data in the General Social Survey. Social Networks, 9, 63-73.
5. Chan, D. (1998). Functional relations among constructs in the same content domain at different levels of analysis: A typology of composition models. Journal of Applied Psychology, 83, 234-246.
6. Collins, L. M., Schafer, J. L., & Kam, C. M. (2001). A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychological Methods, 6, 330-351.
7. Costenbader, E., & Valente, T. W. (2003). The stability of centrality measures when networks are sampled. Social Networks, 25, 283-307.
8. Dawson, J. F., & Newman, D. A. (2006, May). Pairwise deletion problems with moderated multiple regression. In D. A. Newman (Chair), Testing interaction effects: Problems and procedures. Symposium presented at the SIOP Annual Convention, Dallas, TX.
9. Dempster, A. P., Laird, N. H., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, B39, 1-38.
10. Dillman, D. A. (1978). Mail and telephone surveys: The total design method. New York: Wiley.
11. Duvall, S., & Tweedie, R. (2000). Trim and fill: A simple funnel plot based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56, 276-284.
12. Enders, C. K. (2001). A primer on maximum likelihood algorithms for use with missing data. Structural Equation Modeling, 8, 128-141.
13. Foa, E. B., & Foa, U. G. (1980). Resource theory: Interpersonal behavior as exchange. In K. Gergen, M. S. Greenberg, & R. Willis (Eds.), Social exchange: Advances in theory and research (pp. 77-94). New York: Plenum Press.
14. Fox, R. J., Crask, M. R., & Kim, J. (1988). Mail survey response rate: A metaanalysis of selected techniques for inducing response. Public Opinion Quarterly, 52, 467-491.
15. Gold, M. S., & Bentler, P. M. (2000). Treatments of missing data: A Monte Carlo comparison of RBHDI, iterative stochastic regression imputation, and expectation-maximization. Structural Equation Modeling, 7, 319-355.
16. Gold, M. S., Bentler, P. M., & Kim, K. H. (2003). A comparison of maximum-likelihood and asymptotically distribution-free methods of treating incomplete nonnormal data. Structural Equation Modeling, 10, 47-79.
17. Gouldner, A. W. (1960). The norm of reciprocity: A preliminary statement. American Sociological Review, 25, 161-178.
18. Graham, J. W., Cumsille, P. E., & Elek-Fiske, E. (2003). Methods for handling missing data. In J. A. Schinka & W. F. Velicer (Eds.), Research methods in psychology (pp. 87-114). Vol. 2 of Handbook of psychology (I. B. Weiner, Editor in Chief). New York: Wiley.
19. Harrison, D. A., Newman, D. A., & Roth, P. L. (2006). How important are job attitudes? Meta-analytic comparisons of integrative behavioral outcomes and time sequences. Academy of Management Journal, 49, 305-325.
20. Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings (2nd ed.). Newbury Park: Sage.
21. James, L. R., Demaree, R. G., & Wolf, G. (1984). Estimating within-group interrater reliability with and without response bias. Journal of Applied Psychology, 69, 85-98.
22. Judge, T. A., Heller, D., & Mount, M. K. (2002). Five-factor model of personality and job satisfaction: A meta-analysis. Journal of Applied Psychology, 87, 530-541.
23. Lipsey, M. W., & Wilson, D. B. (1993). The efficacy of psychological, educational, and behavioral treatment: Confirmation from meta-analysis. American Psychologist, 48, 1181-1209.
24. Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. New York: Wiley.
25. Little, R. J. A., & Rubin, D. B. (2002). Statistical analysis with missing data (2nd ed.). New York: Wiley.
26. Marsh, H. W. (1998). Pairwise deletion for missing data in structural equation models: Nonpositive definite matrices, parameter estimates, goodness of fit, and adjusted sample sizes. Structural Equation Modeling, 5, 22-36.
27. Martocchio, J. J., & Harrison, D. A. (1993). To be there or not to be there? Questions, theories and methods in absenteeism research. In K. Rowland & G. Ferris (Eds.), Research in personnel and human resources management (Vol. 11, pp. 259-329). Greenwich, CT: JAI Press.
28. Newman, D. A. (2003). Longitudinal modeling with randomly and systematically missing data: A simulation of ad hoc, maximum likelihood, and multiple imputation techniques. Organizational Research Methods, 6,328-362.
29. Newman, D. A. (2004, April). Missing data in longitudinal designs:Enhancing imputation with auxiliary variables. In D. A. Newman & J. L. Farr (Cochairs), Assumptions and conventions in data analysis. Symposium presented at the SIOP Annual Convention, Chicago, IL.
30. Newman, D. A., & Sin, H. P. (2009). How do missing data bias estimates of within-group agreement? Sensitivity of SDWG, CVWG, rWG(J), rWG(J)*, and ICC to systematic nonresponse. Organizational Research Methods.
31. Ostroff, C. (1993). Comparing correlations based on individual-level and aggregated data. Journal of Applied Psychology, 78, 569-582.
32. Robins, G., Pattison, P., & Woolcock, J. (2004). Missing data in networks:Exponential random graph (p*) models for networks with nonrespondents. Social Networks, 26, 257-283.
33. Robinson, W. S. (1950). Ecological correlations and the behaviour of individuals. American Sociological Review, 15, 351-357.
34. Rogelberg, S. G., Conway, J. M., Sederburg, M. E., Spitzmuller, C., Aziz, S., & Knight, W. E. (2003). Profiling active and passive nonrespondents to an organizational survey. Journal of Applied Psychology, 88, 1104-1114.
35. Rogelberg, S. G., Luong, A., Sederburg, M. E., & Cristol, D. S. (2000). Employee attitude surveys: Examining the attitudes of noncompliant employees. Journal of Applied Psychology, 85, 284-293.
36. Roth, P. L., & BeVier, C. A. (1998). Response rates in HRM/OB survey research: Norms and correlates, 1990-1994. Journal of Management, 24, 97-117.
37. Roth, P. L., Switzer, F. S., & Switzer, D. M. (1999). Missing data in multiple item scales: A Monte Carlo analysis of missing data techniques. Organizational Research Methods, 2, 211-232.
38. Rubin, D. B. (1976). Inference and missing data. Biometrika, 63, 581-592.
39. Schafer, J. L. (1997). Analysis of incomplete multivariate data. New York:Chapman & Hall.
40. Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147-177.
41. Schneider, B., Salvaggio, A. N., & Subirats, M. (2002). Climate strength: A new direction for climate research. Journal of Applied Psychology, 87, 220-229.
42. Spitzmuller, C., Glenn, D. M., Barr, C. D., Rogelberg, S. G., & Daniel, P. (2006). "If you treat me right, I reciprocate": Examining the role of exchange in survey response. Journal of Organizational Behavior, 27, 19-35.
43. Stork, D., & Richards, W. D. (1992). Nonrespondents in communication network studies: Problems and possibilities. Group & Organization Management, 17, 193-209.
44. Tett, R. P., & Meyer, J. P. (1993). Job satisfaction, organizational commitment, turnover intention, and turnover: Path analyses based on metaanalytic finding. Personnel Psychology, 46, 259-293.
45. Vevea, J. L., & Woods, C. M. (2005). Publication bias in research synthesis:Sensitivity analysis using a priori weight functions. Psychological Methods, 10, 428-443.
46. Yammarino, F. J., Skinner, S. J., & Childers, T. L. (1991). Understanding mail survey response behavior. Public Opinion Quarterly, 55, 613-629.
47. Yu, J., & Cooper, H. (1983). A quantitative review of research design effects on response rates to questionnaires. Journal of Marketing Research, 20, 36-44.
48. Zimmerman, R. D. (2006). Understanding the impact of personality traits on individuals' turnover decisions. Unpublished doctoral dissertation, University of Iowa.