Finite sample adjustments in estimating equations and covariance estimators for intracluster correlations

Statistics in Medicine

Volumn 27, Issue 27, 2008, Pages 5764-5785

  Preisser, John ^a   Lu, Bing ^b   Qaqish, Bahjat ^a  

^a The University of North Carolina at Chapel Hill   (United States)

^b Brown University Center for Primary Care and Prevention   (United States)

Author keywords

Cluster trials; Correlated binary outcomes; Generalized estimating equations; Intraclass correlation; Sandwich estimators

Indexed keywords

ADOLESCENT; ADULT; AGE; ANALYSIS OF VARIANCE; ARTICLE; CHILD BEHAVIOR; CLINICAL TRIAL; CLUSTER ANALYSIS; COMPARATIVE STUDY; CONFIDENCE INTERVAL; DRINKING BEHAVIOR; EPIDEMIOLOGY; FOLLOW UP; HUMAN; JUVENILE DELINQUENCY; LEGAL ASPECT; MALE; STATISTICAL MODEL; TIME; UNITED STATES;

ADOLESCENT; ADOLESCENT BEHAVIOR; AGE FACTORS; ALCOHOL DRINKING; ANALYSIS OF VARIANCE; BIAS (EPIDEMIOLOGY); CLINICAL TRIALS AS TOPIC; CLUSTER ANALYSIS; CONFIDENCE INTERVALS; FOLLOW-UP STUDIES; HUMANS; JUVENILE DELINQUENCY; MALE; MODELS, STATISTICAL; TIME FACTORS; UNITED STATES; YOUNG ADULT;

EID: 58749099140     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3390     Document Type: Article

References (43)

1. Wang Y-G, Carey V. Working correlation structure misspecification, estimation and covariate design: implications for generalized estimating equations performance. Biometrika 2003; 90:29-41.
2. Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986; 73:13-22.
3. Zhao LP, Prentice RL. Correlated binary regression using a quadratic exponential model. Biometrika 1990; 77:642-648.
4. Liang K-Y, Zeger SL, Qaqish BF. Multivariate regression analyses for categorical data. Journal of the Royal Statistical Society 1992; 54:3-40.
5. Pendergast JF, Gange SJ, Newton MA, Lindstrom MJ, Palta M, Fisher MR. A survey of methods for analyzing clustered binary response data. International Statistical Review 1996; 64:89-118.
6. Prentice RL. Correlated binary regression with covariates specific to each binary observation. Biometrics 1988; 44:1033-1048.
7. Lipsitz SR, Fitzmaurice GM. Estimating equations for measures of association between repeated binary responses. Biometrics 1996; 52:903-912.
8. Lipsitz SR, Molenberghs G, Fitzmaurice GM, Ibrahim J. GEE with Gaussian estimation of the correlations when data are incomplete. Biometrics 2000; 52:528-536.
9. Shults J, Whitt MC, Kumanyika S. Analysis of data with multiple sources of correlation in the framework of generalized estimating equations. Statistics in Medicine 2004; 23:3209-3226.
10. Carey V, Zeger SL, Diggle P. Modeling multivariate binary data with alternative logistic regression. Biometrika 1993; 80:517-526.
11. Ten Have TR. Marginal and conditional association models for analyzing departures from exchangeability of tooth bone loss. Applied Statistics 1996; 45:353-369.
12. Martus P, Stroux A, J̈unemann AM, Korth M, Jonas JB, Horn FK, Ziegler A. GEE approaches to marginal regression models for medical diagnostic tests. Statistics in Medicine 2004; 23:1377-1398.
13. Albert PS, McShane LM. A generalized estimating equations approach for spatially correlated binary data: applications to the analysis of neuroimaging. Biometrics 1995; 51:627-638.
14. Podgor MJ, Remaley NA, Chew E. Associations between siblings for esotropia and exotropia. Archives of Ophthalmology 1996; 114:739-744.
15. Donner A, Klar N. Design and Analysis of Cluster Randomization Trials in Health Research. Arnold: London, 2000.
16. Murray DM. Design and Analysis of Group-randomized Trials. Oxford University Press: New York, 1998.
17. Wolfson M, Altman D, DuRant R, Shrestha A, Patterson TE, Williams A, Zaccaro D, Hensberry R, Suerken C, Foley K, Preisser J, Brown S. National Evaluation of the Enforcing Underage Drinking Laws Program: Year 4 Report. Wake Forest University School of Medicine, Winston-Salem, NC, 2004. Available from: http://www.phsintranet.wfubmc.edu/EUDL2/pubs.cfm (Accessed 2 February 2007).
18. Preisser JS, Young ML, Zaccaro DJ, Wolfson M. An integrated population-averaged approach to the design, analysis and sample size determination of cluster-unit trials. Statistics in Medicine 2003; 22:1235-1254.
19. Preisser JS, Reboussin BA, Song E-Y, Wolfson M. The importance and role of intracluster correlations in planning cluster trials. Epidemiology 2007; 18:552-560.
20. Zeger SL, Liang K-Y, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics 1988; 44:1049-1060.
21. Neuhaus JM, Kalbfleisch JD, Hauck WW. A comparison of cluster-specific and population averaged approaches for analyzing correlated binary data. International Statistical Review 1991; 59:25-36.
22. Heagerty PJ. Marginally specified logistic-normal models for longitudinal binary data. Biometrics 1999; 55: 688-698.
23. Heagerty PJ, Zeger SL. Marginalized multilevel models and likelihood inference. Statistical Science 2000; 15:1-26.
24. Ridout MS, Demetrio CGB, Firth D. Estimating intraclass correlation for binary data. Biometrics 1999; 55: 137-148.
25. Zou G, Donner A. Confidence interval estimation of the intraclass correlation coefficient for binary outcome data. Biometrics 2004; 60:807-811.
26. Bellamy SL, Gibberd R, Hancock L, Howley P, Kennedy B, Klar N, Lipsitz S, Ryan L. Analysis of dichotomous outcome data for community intervention studies. Statistical Methods in Medical Research 2000; 9:135-159.
27. Ukoumunne OC, Thompson SG. Analysis of cluster randomized trials with repeated cross-sectional binary measurements. Statistics in Medicine 2001; 20:417-433.
28. Chaix B, Bobashev G, Merlo J, Chauvin P. Re: Detecting patterns of occupational illness clustering with alternating logistic regressions applied to longitudinal data. American Journal of Epidemiology 2004; 160:505-506.
29. Preisser JS. Author Reply. Re: Detecting patterns of occupational illness clustering with alternating logistic regressions applied to longitudinal data. American Journal of Epidemiology 2004; 160:506-507.
30. Goldstein H, Rasbash J. Improved approximations for multilevel models with binary responses. Journal of the Royal Statistical Society, Series A 1996; 159:505-513.
31. Wright D, Bobashev GV, Novak SP. Decomposing the total variation in a nested random effects model of neighborhood, household, and individual components when the dependent variable is dichotomous: implications for adolescent marijuana use. Drug and Alcohol Dependence 2005; 78:195-204.
32. Qaqish BF. A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations. Biometrka 2003; 90:455-463.
33. Feng Z, Diehr P, Peterson A, McLerran D. Selected statistical issues in group randomized trials. Annual Review of Public Health 2001; 22:167-187.
34. Evans BA, Feng Z, Peterson AV. A comparison of generalized linear mixed model procedures with estimating equations for variance and covariance parameter estimation in longitudinal studies and group randomized trials. Statistics in Medicine 2001; 20:3353-3373.
35. Sharples K, Breslow N. Regression analysis of correlated binary data: some small samples results for the estimating equation approach. Journal of Statistical Computation and Simulation 1992; 42:1-20.
36. Kauermann G, Carroll RJ. A note on the efficiency of sandwich covariance matrix estimation. Journal of the American Statistical Association 2001; 96:1387-1398.
37. Mancl LA, DeRouen TA. A covariance estimator for GEE with improved small-sample properties. Biometrics 2001; 57:126-134.
38. Lu B, Preisser JS, Qaqish BF, Suchindran C, Bangdiwala SI, Wolfson M. A comparison of two bias-corrected covariance estimators for generalized estimating equations. Biometrics 2007; 63:935-941.
39. Yan J, Fine J. Estimating equations for association structures. Statistics in Medicine 2004; 23:859-874.
40. Preisser JS, Qaqish BF. Deletion diagnostics for generalised estimating equations. Biometrika 1996; 83:551-562.
41. Fay MP, Graubard BI. Small-sample adjustments for Wald-type tests using sandwich estimators. Biometrics 2001; 57:1198-1206.
42. Pan W, Wall MM. Small-sample adjustments in using the sandwich variance estimator in generalized estimating equations. Statistics in Medicine 2002; 21:1429-1441.
43. Preisser JS, Qaqish BF, Perin J. A note on deletion diagnostics for estimating equations. Biometrika 2008; 95:509-513.