Can the buck always be passed to the highest level of clustering?

BMC Medical Research Methodology

Volumn 16, Issue 1, 2016, Pages

  Bottomley, Christian ^a   Kirby, Matthew J ^a   Lindsay, Steve W ^a   Alexander, Neal ^a  

^a LONDON SCHOOL OF HYGIENE AND TROPICAL MEDICINE   (United Kingdom)

Author keywords

Clustering; Hierarchical; Logistic regression; Multilevel; Robust variance estimate; Sandwich estimator

Indexed keywords

CHILD; CLUSTER ANALYSIS; COMPARATIVE STUDY; COMPUTER SIMULATION; CONTROLLED STUDY; FEMALE; GAMBIA; HUMAN; INCIDENCE; INFANT; MALARIA; MALE; MASS SCREENING; PRESCHOOL CHILD; PROCEDURES; RANDOMIZED CONTROLLED TRIAL; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; UNITED KINGDOM;

CHILD; CHILD, PRESCHOOL; CLUSTER ANALYSIS; COMPUTER SIMULATION; FEMALE; GAMBIA; HUMANS; INCIDENCE; INFANT; LOGISTIC MODELS; MALARIA; MALE; MASS SCREENING; MODELS, STATISTICAL; SENSITIVITY AND SPECIFICITY; UNITED KINGDOM;

EID: 84960108583     PISSN: None     EISSN: 14712288     Source Type: Journal    
DOI: 10.1186/s12874-016-0127-1     Document Type: Article

References (22)

1. Eldridge SM, Ukoumunne OC, Carlin JB. The intra-cluster correlation coefficient in cluster randomised trials: a review of definitions. Int Stat Rev. 2009; 77(3):378-394.
2. Moulton BR. Random group effects and the precision of regression estimates. J Econ. 1986; 32(3):385-397.
3. Scott AJ, Holt D. The effect of two-stage sampling on ordinary least squares methods. J Am Stat Assoc. 1982; 77(380):848-854.
4. Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika. 1986; 73(1):13-22.
5. Angrist JD, Pischke JS. Mostly harmless econometrics. 6 Oxford Street, Woodstock, Oxfordshire OX20 1TW: Princeton University Press; 2009.
6. Bell RM, McCaffrey DF. Bias reduction in standard errors for linear regression with multi-stage samples. Surv Methodol. 2002; 28(2):169-181.
7. Hubbard AE, Ahern J, Fleischer NL, Van der Laan M, Lippman SA, Jewell N, et al.To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology. 2010; 21(4):467-74.
8. Zeger SL, Liang KY, Albert PS. Models for longitudinal data: a generalized estimating equation approach. Biometrics. 1988; 44(4):1049-60.
9. Adams G, Gulliford MC, Ukoumunne OC, Eldridge S, Chinn S, Campbell MJ. Patterns of intra-cluster correlation from primary care research to inform study design and analysis. J Clin Epidemiol. 2004; 57(8):785-94.
10. Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing. Austria: Vienna; 2015. http://www.R-project.org/. Accessed 24 Feb 2016.
11. Harrell FE. rms: Regression Modeling Strategies. R package version 4.4-0. 2015. http://CRAN.R-project.org/package=rms. Accessed 24 Feb 2016.
12. Kirby MJ, Ameh D, Bottomley C, Green C, Jawara M, Milligan PJ, et al.Effect of two different house screening interventions on exposure to malaria vectors and on anaemia in children in The Gambia: a randomised controlled trial. Lancet. 2009; 374(9694):998-1009.
13. Pan W, Wall MM. Small-sample adjustments in using the sandwich variance estimator in generalized estimating equations. Stat Med. 2002; 21(10):1429-1441.
14. McCaffrey DF, Bell RM. Improved hypothesis testing for coefficients in generalized estimating equations with small samples of clusters. Stat Med. 2006; 25(23):4081-4098.
15. Fay MP, Graubard BI. Small-sample adjustments for Wald-type tests using sandwich estimators. Biometrics. 2001; 57(4):1198-1206.
16. Mancl LA, DeRouen TA. A covariance estimator for GEE with improved small-sample properties. Biometrics. 2001; 57(1):126-134.
17. Cameron AC, Miller DL. A practitioner's guide to cluster-robust inference. J Hum Resour. 2015; 50(2):317-372.
18. Qaqish BF, Liang KY. Marginal models for correlated binary responses with multiple classes and multiple levels of nesting. Biometrics. 1992; 48(3):939-50.
19. Chao EC. Structured correlation in models for clustered data. Stat Med. 2006; 25(14):2450-68.
20. Stoner JA, Leroux BG, Puumala M. Optimal combination of estimating equations in the analysis of multilevel nested correlated data. Stat Med. 2010; 29(4):464-73.
21. McDonald BW. Estimating logistic regression parameters for bivariate binary data. J R Stat Soc Ser B. 1993; 55(2):391-397.
22. Fitzmaurice GM. A caveat concerning independence estimating equations with multivariate binary data. Biometrics. 1995; 51(1):309-317.