Analysis of pregnancy and other factors on detection of human papilloma virus (HPV) infection using weighted estimating equations for follow-up data

Statistics in Medicine

Volumn 22, Issue 13, 2003, Pages 2217-2233

  Ziegler, Andreas ^a   Kastner, Christian ^b,d   Chang Claude, Jenny ^c  

^a UNIVERSITY OF LÜBECK   (Germany)

^b UNIVERSITY OF MUNICH   (Germany)

^c GERMAN CANCER RESEARCH CENTER DKFZ   (Germany)

^d NONE   (Germany)

Author keywords

Correlated data analysis; Generalized estimating equations; Horvitz Thompson estimation; Marginal models; Missing data; Weighted estimating equations

Indexed keywords

ARTICLE; CASE STUDY; CONFIDENCE INTERVAL; DATA ANALYSIS; DNA HYBRIDIZATION; FEMALE; FOLLOW UP; HUMAN; LONGITUDINAL STUDY; PAPANICOLAOU TEST; PREGNANCY; PROBABILITY; RANDOMIZATION; RISK FACTOR; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL PARAMETERS; VIRUS DETECTION; VIRUS INFECTION; WART VIRUS;

COHORT STUDIES; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; LONGITUDINAL STUDIES; MONTE CARLO METHOD; PAPILLOMAVIRIDAE; PAPILLOMAVIRUS INFECTIONS; PREGNANCY; PREGNANCY COMPLICATIONS, INFECTIOUS; REGRESSION ANALYSIS; TUMOR VIRUS INFECTIONS;

EID: 0038726174     PISSN: 02776715     EISSN: None     Source Type: Journal    
DOI: 10.1002/sim.1409     Document Type: Article

References (47)

1. Zeger SL, Liang K-Y, Self SG. The analysis of binary longitudinal data with time-independent covariates. Biometrika 1985; 72:31-38.
2. Liang K-Y, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika 1986; 73:13-22.
3. Ziegler A, Kastner C, Brunner D, Blettner M. Familial associations of lipid profiles: a generalized estimating equations approach. Statistics in Medicine 2000; 19:3345-3357.
4. Laird NM. Missing data in longitudinal studies. Statistics in Medicine 1988; 7:305-315.
5. Robins JM, Rotnitzky AG, Zhao LP. Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. Journal of the American Statistical Association 1995; 90:106-120.
6. Robins JM. Correcting for non-compliance in randomized trials using structural nested mean models. Communications in Statistics, Part A - Theory and Methods 1994; 23:2379-2412.
7. Robins JM, Rotnitzky AG. Semiparametric efficiency in multivariate regression models with missing data. Journal of the American Statistical Association 1995; 90:122-129.
8. Rotnitzky AG, Robins JM. Semiparametric estimation of models for means and covariances in the presence of missing data. Scandinavian Journal of Statistics 1995; 22:323-333.
9. Zhao LP, Lipsitz SR, Lew D. Regression analysis with missing covariate data using estimating equations. Biometrics 1996; 52:1165-1182.
10. Carlin JB, Wolfe R, Coffey C, Patton GC. Analysis of binary outcomes in longitudinal studies using weighted estimating equations and discrete-time survival methods: prevalence and incidence of smoking in an adolescent cohort. Statistics in Medicine 1999; 18:2655-2679.
11. Paik MC. The generalized estimating equation approach when data are not missing completely at random. Journal of the American Statistical Association 1997; 92:1320-1329.
12. Xie F, Paik MC. Multiple imputation methods for the missing covariates in generalized estimating equation. Biometrics 1997; 53:1538-1546.
13. Horvitz DG, Thompson DJ. A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association 1952; 47:663-685.
14. Chang-Claude J, Schneider A, Smith E, Blettner M, Wahrendorf J, Turek L. Longitudinal study of the effects of pregnancy and other factors on detection of HPV. Gynecologic Oncology 1996; 60:355-362.
15. Kastner C, Fieger A, Heumann C. MAREG and WinMAREG - a tool for marginal regression models. Computational Statistics and Data Analysis 1997; 24:235-241. (URL: http://www.stat.unimuenchen.de/~andreas/mareg/winmareg.html).
16. Barber SR, Werdel J, Symbula M, Williams J, Burkett BA, Taylor PT. Seroreactivity to HPV-16 proteins in women with early cervical neoplasia. Cancer Immunology, Immunotherapy 1992; 35:33-38.
17. Garry R, Jones R. Relationship between cervical condylomata, pregnancy and subclinical papillomavirus infection. Journal of Reproductive Medicine 1985; 30:393-399.
18. Schneider A, Hotz M, Gissman L. Increased prevalence of human papillomaviruses in the lower genital tract of pregnant women. International Journal of Cancer 1987; 40:198-201.
19. Koutsky LA, Holmes KK, Critchlow CW, Stevens CE, Paavonen J, Beckmann AM. A cohort study of the risk of cervical intreapithelial neoplasia grade 2 or 3 in relation to papillomavirus infection. New England Journal of Medicine 1992; 327:1272-1278.
20. zur Hausen H. Viruses in human cancers. Science 1991; 254:1167-1173.
21. Gissmann L, Wolnik L, Ikenberg H, Koldovsky U, Schnurch HG, zur Hausen H. Human papillomavirus types 6 and 11 DNA sequences in genital and laryngeal papillomas and in some cervical cancers. Proceedings of the National Academy of Sciences of the United States of America 1983; 80:560-563.
22. Fahrmeir L, Tutz G. Multivariate Statistical Modelling Based on Generalized Linear Models. Springer: New York, 1994.
23. Ziegler A, Kastner C, Blettner M. The generalised estimating equations: an annotated bibliography. Biometrical Journal 1998; 40:115-139.
24. Crowder MJ. On the use of a working correlation matrix in using generalized linear models for repeated measurements. Biometrika 1995; 82:407-410.
25. Pepe MS, Anderson GL. A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data. Communications in Statistics, Part B - Simulation and Computation 1994; 23:939-951.
26. Pan W, Louis TA, Connett JE. A note on marginal regression with correlated response data. American Statistician 2000; 54:191-195.
27. Fitzmaurice GM. A caveat concerning independence estimating equations with multivariate binary data. Biometrics 1995; 51:309-317.
28. Mancl LA, Leroux BG. Efficiency of regression estimates for clustered data. Biometrics 1996; 52:500-511.
29. Kalbfleisch JD, Prentice RL. The Statistical Analysis of Failure Time Data. Wiley: New York, 1980.
30. Park CG, Park T, Shin DW. A simple method for generating correlated binary variates. Journal of the American Statistical Association 1996; 50:306-310.
31. Gange SJ, Linton KLP, Scott AJ, DeMets DL, Klein R. A comparison of methods for correlated ordinal measures with ophtalmic applications. Statistics in Medicine 1995; 14:1961-1974.
32. Lee AJ, Scott AJ, Soo S. Comparing Liang-Zeger estimates with maximum likelihood in bivariate logistic regression. Statistical Computation and Simulation 1993; 44:133-148.
33. Emrich LJ, Piedmonte MR. A method for generating high-dimensional multivariate binary variates. American Statistician 1991; 45:302-304.
34. Fitzmaurice GM, Laird NM. A likelihood-based method for analysing longitudinal binary responses. Biometrika 1993; 80:141-151.
35. SunOS. SunOS Reference Manual. Sun Microsystems: Mountain View, 1995.
36. De Villiers EM, Wagner D, Schneider A. Human papillomavirus infections in women without and with abnormal cervical cytology. Lancet 1987; 1:703-7052.
37. Ziegler A, Blettner M, Kastner C, Chang-Claude J. Identifying influential families using regression diagnostics for generalized estimating equations. Genetic Epidemiology 1998; 15:341-353.
38. Diggle PJ, Kenward MG. Informative dropout in longitudinal data analysis. Applied Statistics 1994; 43:49-94.
39. Fitzmaurice GM, Laird NM, Lipsitz SR. Analysing incomplete longitudinal binary responses: a likelihood-based approach. Biometrics 1994; 50:601-612.
40. Fitzmaurice GM, Clifford P, Heath AF. Logistic regression models for binary panel data with attrition. Journal of the Royal Statistical Society, Series A 1996; 159:249-263.
41. Heyting A, Tolboom JTBM, Essers JGA. Statistical handling of drop-outs in longitudinal clinical trials. Statistics in Medicine 1992; 11:2043-2061.
42. Flanders WD, Greenland S. Analytic methods for two-stage case-control studies and other stratified designs. Statistics in Medicine 1991; 10:739-747.
43. Zhao LP, Prentice RL, Self SG. Multivariate mean parameter estimation by using a partly exponential model. Journal of the Royal Statistical Society, Series B 1992; 54:805-811.
44. Little RJA. Survey nonresponse adjustments for estimates of means. International Statistical Review 1986; 54:139-158.
45. Li KC, Duan N. Regression analysis under link violation. Annals of Statistics 1989; 17:1009-1052.
46. Ziegler A, Kastner C. The effect of misspecified response probabilities on parameter estimates from weighted estimating equations. In Correlated Data Modelling, Gregori D, Carmeci G, Friedl H, Ferligoj A, Wedlin A (eds). Franco Angeli: Milano, 2002, 103-119.
47. Sethi S, Müller M, Schneider A, Blettner M, Smith E, Turek L, Wahrendorf J, Gissmann L, Chang-Claude J. Serological response to the E4, E6 and E7 proteins of human papillomavirus (HPV) type 16 in pregnant women. American Journal of Obstetrics and Gynecology 1998; 179:360-364.