Longitudinal data analysis for generalized linear models under participant-driven informative follow-up: An application in maternal health epidemiology

American Journal of Epidemiology

Volumn 171, Issue 2, 2010, Pages 189-197

  Bůžková, Petra ^a   Brown, Elizabeth R ^a   John Stewart, Grace C ^a,b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF WASHINGTON SCHOOL OF MEDICINE   (United States)

Author keywords

Data analysis; Data interpretation, statistical; Epidemiologic methods; Follow up studies; Generalized estimating equation; Generalized linear model; Longitudinal studies; Models, statistical

Indexed keywords

DATA INTERPRETATION; DISEASE PREVALENCE; EPIDEMIOLOGY; HUMAN IMMUNODEFICIENCY VIRUS; MATERNAL HEALTH; PNEUMONIA; REGRESSION ANALYSIS;

ADULT; ARTICLE; BRONCHITIS; DATA ANALYSIS; DIARRHEA; FEMALE; HUMAN; HUMAN IMMUNODEFICIENCY VIRUS 1; KENYA; LONGITUDINAL STUDY; MAJOR CLINICAL STUDY; MALARIA; MASTITIS; MATERNAL WELFARE; PNEUMONIA; TUBERCULOSIS; UPPER RESPIRATORY TRACT INFECTION;

ADULT; FEMALE; HIV INFECTIONS; HIV-1; HUMANS; KENYA; LINEAR MODELS; LONGITUDINAL STUDIES; MATERNAL WELFARE; PREVALENCE;

KENYA;

HUMAN IMMUNODEFICIENCY VIRUS 1;

EID: 73949111609     PISSN: 00029262     EISSN: 14766256     Source Type: Journal    
DOI: 10.1093/aje/kwp353     Document Type: Article

References (17)

1. Liang KY, Zeger SL. Longitudinal data analysis using generalized linear models. Biometrika. 1986;73(1):13-22.
2. Hoffman EB, Sen PK, Weinberg CR. Within-cluster resampling. Biometrika. 2001;88(4):1121-1134.
3. Bužková P, Lumley T. Longitudinal data analysis for generalized linear models with follow-up dependent on outcome-related variables. Can J Stat. 2007;35(4):485-500.
4. Buzková P, Lumley T. Semiparametric modeling of repeated measurements under outcome-dependent follow-up. Stat Med. 2009;28(6):987-1003.
5. Bužková P, Lumley T. Semiparametric loglinear regression for longitudinal measurements subject to irregular, biased follow-up. J Stat Plan Inference. 2008;138(8):2450-2461.
6. Otieno PA, Brown ER, Mbori-Ngacha DA, et al. HIV-1 disease progression in breast-feeding and formula-feeding mothers: a prospective 2-year comparison of T cell subsets, HIV-1 RNA levels, and mortality. J Infect Dis. 2007;195(2): 220-229.
7. Walson JL, Brown ER, Otieno PA, et al. Morbidity among HIV-1-infected mothers in Kenya: prevalence and correlates of illness during 2-year postpartum follow-up. J Acquir Immune Defic Syndr. 2007;46(2):208-215.
8. World Health Organization. Integrated Management of Adolescent and Adult Illness. Interim Guidelines for First-Level Facility Health Workers at Health Centre and District Outpatient Clinic. Geneva, Switzerland: World Health Organization; 2004. (http://www.who.int/hiv/pub/imai/en/ acutecarerev2-e.pdf). (Accessed April 10, 2009).
9. Rubin DB. Inference and missing data. Biometrika. 1976;63(3): 581-592.
10. R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Project for Statistical Computing; 2007. (http://www.R-project.org). (Accessed May 12, 2009).
11. Robins JM, Rotnitzky A, Zhao LP. Analysis of semiparametric regression-models for repeated outcomes in the presence of missing data. J Am Stat Assoc. 1995;90(429):106-121.
12. Rotnitzky A, Robins JM, Scharfstein DO. Semiparametric regression for repeated outcomes with nonignorable nonre-sponse. J Am Stat Assoc. 1998;93(444):1321-1339.
13. Lin DY, Wei LJ, Yang I, et al. Semiparametric regression for the mean and rate functions of recurrent events. J R Stat Soc B Series. 2000;62(4):711-730.
14. Lin H, Scharfstein DO, Rosenheck RA. Analysis of longitudinal data with irregular, outcome-dependent follow-up. J R Stat Soc Series B. 2004;66(3):791-813.
15. Sun J, Sun L, Liu D. Regression analysis of longitudinal data in the presence of informative observation and censoring times. J Am Stat Assoc. 2007;102(480):1397-1406.
16. Liang Y, Lu W, Ying Z. Joint modeling and analysis of longitudinal data with informative observation times. Biometrics. 2009;65(2):377-384.
17. Cole SR, Hernán MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol. 2008; 168(6):656-664.