Logistic regression vs other generalized linear models to estimate prevalence rate ratios;Regression logistique vs autres modeles lineaires generalises pour l'estimation de rapports de prevalences

Revue d'Epidemiologie et de Sante Publique

Volumn 47, Issue 6, 1999, Pages 593-604

  Traissac, P ^a   Martin Prevel Y ^a   Delpeuch, F ^a   Maire, B ^a  

^a INSTITUT DE RECHERCHE POUR LE DÉVELOPPEMENT   (France)

Author keywords

Cross sectional study; Generalized linear model; Logistic regression; Odds ratio; Prevalence rate ratio

Indexed keywords

ARTICLE; PREVALENCE; REGRESSION ANALYSIS; STATISTICAL MODEL; HUMAN;

HUMANS; PREVALENCE; REGRESSION ANALYSIS;

EID: 0342545928     PISSN: 03987620     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (25)

1. Bouyer J, Hémon D, Cordier S et al. Épidémiologie. Principes et méthodes quantitatives. Paris : Editions INSERM ; 1995.
2. Lee J. Odds ratio or relative risk for cross-sectional data? [letter] [see comments]. Int J Epidemiol 1994; 23: 201-3.
3. Lee J. Estimation of prevalence rate ratios from cross sectional data: a reply [letter]. Int J Epidemiol 1995; 24: 1066-67.
4. Osborn J, Cattaruzza MS. Odds ratio and relative risk for cross-sectional data [letter; comment]. Int J Epidemiol 1995; 24: 464-5.
5. Zocchetti C, Consonni D, Bertazzi PA. Estimation of prevalence rate ratios from cross-sectional data [letter; comment]. Int J Epidemiol 1995; 24: 1064-7.
6. Hughes K. Odds ratios in cross-sectional studies [letter; comment]. Int J Epidemiol 1995; 24: 463-8.
7. Thompson ML, Myers JE, Kriebel D. Prevalence odds ratio or prevalence ratio in the analysis of cross sectional data: what is to be done? Occup Environ Med 1998; 55: 272-7.
8. Zocchetti C, Consonni D, Bertazzi PA. Relationship between prevalence rate ratios and odds ratios in cross-sectional studies. Int J Epidemiol 1997; 26: 220-3.
9. OMS. Utilisation et interprétation de l'anthropométrie. Genève : OMS ; 1995.
10. Bouyer J. La régression logistique en épidémiologie. I. Rev Epidemiol Sante Publique 1991 ; 39 : 79-87.
11. Bouyer J. La régression logistique en épidémiologie. II. Rev Epidemiol Sante Publique 1991 ; 39 : 183-96.
12. Lemeshow S, Hosmer DW. Applied Logistic Regression: Wiley; 1989.
13. Mc Cullagh P, Nelder JA. Generalized Linear Models. Second Edition ed: Chapman & Hall; 1989.
14. Dobson AJ. An introduction to generalized linear models. London: Chapman & Hall: 1990.
15. Cook RJ. Generalized Linear Model. In: Armitage P, Colton T, editors. Encyclopedia of Biostatistics: Wiley; 1998. p. 1637-1650.
16. Richardson S. Développements récents de la biostatistique. Rev Epidemiol Sante Publique 1996; 44: 482-93.
17. SAS Institute. SAS/STAT Software: changes and enhancements through release 6.12. Cary N.C.: SAS Institute; 1997.
18. Simonoff JS. Logistic regression, categorical predictors and goodness-of-fit: it depends on who you ask. The American Statistician 1998; 52: 10-4.
19. Skov T, Deddens J, Petersen MR, Endahl L. Prevalence proportion ratios: estimation and hypothesis testing. Int J Epidemiol 1998; 27: 91-5.
20. Viel JF. La régression de Poisson en épidémiologie. Rev Epidemiol Sante Publique 1994; 42 (1): 79-87.
21. Martuzzi M, Elliott P. Estimating the incidence rate ratio in cross-sectional studies using a simple alternative to logistic regression. Ann Epidemiol 1998; 8: 52-5.
22. Kleinbaum DA, Kupper LL, Morgenstern H. Epidemiologic research. Principles and quantitative methods. New York: Van Nostrand Reinhold; 1982.
23. Dean CB. Overdispersion. In: Armitage P, Colton T, editors. Encyclopedia of Biostatistics: Wiley; 1998. p. 3226-3232.
24. SAS Institute. SAS/STAT User's Guide, Version 6, Volume 1 & 2. Fourth Edition ed. Cary NC: SAS Institute Inc.; 1989.
25. SAS Institute. Categorical data analysis using the SAS system. Cary N.C.: SAS Institute; 1995.60@