Performance of weighted estimating equations for longitudinal binary data with drop-outs missing at random

Statistics in Medicine

Volumn 21, Issue 20, 2002, Pages 3035-3054

  Preisser, John S ^a   Lohman, Kurt K ^b   Rathouz, Paul J ^c  

^a IL   (United States)

^b WAKE FOREST SCHOOL OF MEDICINE   (United States)

^c UNIVERSITY OF CHICAGO   (United States)

Author keywords

Correlated data; Drop outs; Estimating equations; Logistic models; Repeated measures

Indexed keywords

ARTICLE; CIGARETTE SMOKING; CONTROLLED STUDY; CORRELATION ANALYSIS; DATA ANALYSIS; FINITE ELEMENT ANALYSIS; LONGITUDINAL STUDY; MATHEMATICAL COMPUTING; OBSERVATION; PROBABILITY; SAMPLE SIZE; SIMULATION; SMOKING HABIT; STATISTICAL ANALYSIS; STATISTICAL MODEL; TIME;

COMPUTER SIMULATION; FEMALE; HUMANS; LONGITUDINAL STUDIES; MALE; MODELS, STATISTICAL; PATIENT DROPOUTS;

EID: 0037202104     PISSN: 02776715     EISSN: None     Source Type: Journal    
DOI: 10.1002/sim.1241     Document Type: Article

References (22)

1. Diggle PJ, Liang K-Y, Zeger SL. Analysis of Longitudinal Data. Oxford University Press: Oxford, 1994.
2. Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986; 73:13-22.
3. Hendricks SA, Wassell JT, Collins JW, Sedlak SL. Power determinations for geographically clustered data using generalized estimating equations. Statistics in Medicine 1996; 15:1951-1960.
4. Carr GJ, Portier CJ. An evaluation of some methods for fitting dose-response models to quantal-response developmental toxicology data. Biometrics 1993; 49:779-791.
5. Bieler GS, Williams RL. Cluster sampling techniques in quantal response teratology and developmental toxicity studies. Biometrics 1995; 51:764-776.
6. Sharples K, Breslow N. Regression analysis of correlated binary data: some small sample results for the estimating equation approach. Journal of Statistical Computation and Simulation 1992; 42:1-20.
7. Emrich LJ, Piedmonte MR. On some small sample properties of generalized estimating equation estimates for multivariate dichotomous outcomes. Journal of Statistical Computation and Simulation 1992; 41:19-29.
8. Lipsitz SR, Fitzmaurice GM, Orav EJ, Laird NM. Performance of generalized estimating equations in practical situations. Biometrics 1994; 50:270-278.
9. Gunsolley JC, Getchell C, Chinchilli VM. Small sample characteristics of generalized estimating equations. Communications in Statistics-Simulations 1995; 24:869-878.
10. Lipsitz SR, Molenberghs G, Fitzmaurice GM, Ibrahim J. GEE with Gaussian estimation of the correlations when data are incomplete. Biometrics 2000; 56:528-536.
11. Preisser JS, Galecki AT, Lohman KK, Wagenknecht LE. Analysis of smoking trends with incomplete longitudinal binary responses. Journal qf the American Statistical Association 2000; 95:1021-1031.
12. Robins JM, Rotnitzky A, Zhao LP. Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. Journal of the American Statistical Association 1995; 90:106-121.
13. Fitzmaurice GM, Molenberghs G, Lipsitz SR. Regression models for longitudinal binary responses with informative drop-outs. Journal of the Royal Statistical Society, Series B 1995; 57:691-704.
14. Troxel AB. A comparative analysis of quality of life data from a southwest oncology group randomized trial of advanced colorectal cancer. Statistics in Medicine 1998; 17:767-779.
15. O'Hara-Hines RJ, Hines WGS, Friesen TG. A comparison of two drop-out weighting schemes in the analysis of clustered data with categorical and continuous responses. Journal of Agricultural, Biological, and Environmental Statistics 1999; 4:203-216.
16. Miller ME, Ten Have TR, Reboussin BA, Lohman KK, Rejeski WJ. A marginal model for analyzing discrete outcomes from longitudinal surveys with outcomes subject to multiple cause non-response. Journal of the American Statistical Association 2001; 96:844-857.
17. Little RJA, Rubin DB. Statistical Analysis with Missing Data. Wiley: New York, 1987.
18. Troxel AB, Lipsitz SR, Brennan TA. Weighted estimating equations with nonignorably missing response data. Biometrics 1997; 53:857-869.
19. Rotnitzky A, Robins JM, Scharfstein DO. Semiparametric regression for repeated outcomes with nonignorable nonresponse. Journal of the American Statistical Association 1998; 93:1321-1339.
20. McCullagh P, Nelder JA. Generalized Linear Models. 2nd edn. Chapman and Hall: London, 1989.
21. Mancl LA, DeRouen TA. A covariance estimator for GEE with improved small-sample properties. Biometrics 2001; 57:126-134.
22. Robins JM, Rotnitzky A. Semiparametric efficiency in multivariate regression models with missing data. Journal of the American Statistical Association 1995; 90:106-121.