Assessing treatment effects in randomized longitudinal two-group designs with missing observations

Journal of Modern Applied Statistical Methods

Volumn 3, Issue 2, 2004, Pages 271-287

  Algina, James ^a   Keselman, H J ^b  

^a UNIVERSITY OF FLORIDA   (United States)

^b UNIVERSITY OF MANITOBA   (Canada)

Author keywords

Missing data; PROC MIXED; Randomized designs; Repeated measurements

Indexed keywords

EID: 18344391049     PISSN: 15389472     EISSN: None     Source Type: Journal    
DOI: 10.22237/jmasm/1099267380     Document Type: Article

References (14)

1. Ahn, C., Tonidandel, S., Overall, J. E. (2000). Issues in use of SAS Proc.Mixed to test the significance of treatment effects in controlled clinical trials. Journal of Biopharmaceutical Statistics, 10, 265-286.
2. Algina, J. Keselman, H. J., & Othman, A. R. (2003). Analyzing group by time effects in longitudinal two-group randomized trial designs with missing data. Journal of Modern Applied Statistical Methods, 2, 50-72.
3. Hedeker, D., & Gibbons, R. D. (1997). Application of random-effects pattern-mixture models for missing data in longitudinal studies. Psychological Methods, 2, 64-78.
4. Littell, R. C., Milliken, G. A., Stroup, W. W., & Wolfinger, R. D. (1996). SAS system for mixed models. Cary, NC: SAS Inc.
5. Little, R. J. A. (1995). Modeling the drop-out mechanism in repeated-measures studies. Journal of the American Statistical Association, 90, 1112-1121.
6. Little, R. J. A. (1993). Pattern-mixture models for multivariate incomplete data. Journal of the American Statistical Association, 88, 125-134.
7. Little, R. J. A. (1994). A class of pattern-mixture models for normal incomplete data. Biometrics, 81, 471-483.
8. Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. New York: Wiley,
9. Overall, J. E., Ahn, C., Shivakumar, C., Kalburgi, Y. (1999). Problematic formulations of SAS Proc.Mixed models for repeated measurements. Journal of Biopharmaceutical Statistics, 9, 189-216.
10. Overall, J. E., Ghasser, S., Fiore, J. (1996). Random regression with imputed values for dropouts. Psychopharmacology Bulletin, 1, 377-388.
11. Rubin, D. B. (1976). Inference and missing data. Biometrika, 63, 581-592.
12. SAS Institute. (1995). Introduction to the MIXED procedure: Course Notes. Cary, NC: Author.
13. Schafer, J. L. (1997). Analysis of incomplete multivariate data. New York: Chapman & Hall/CRC.
14. Verbeke, G., & Molenberghs. (2000). Linear mixed models for longitudinal data. New York: Springer.