207 related articles for article (PubMed ID: 19736577)
1. A practical guide for multivariate analysis of dichotomous outcomes.
Lee J; Tan CS; Chia KS
Ann Acad Med Singap; 2009 Aug; 38(8):714-9. PubMed ID: 19736577
[TBL] [Abstract][Full Text] [Related]
2. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio.
Barros AJ; Hirakata VN
BMC Med Res Methodol; 2003 Oct; 3():21. PubMed ID: 14567763
[TBL] [Abstract][Full Text] [Related]
3. Negative log-binomial model with optimal robust variance to estimate the prevalence ratio, in cross-sectional population studies.
Ibáñez-Pinilla M; Villalba-Niño S; Olaya-Galán NN
BMC Med Res Methodol; 2023 Oct; 23(1):219. PubMed ID: 37794385
[TBL] [Abstract][Full Text] [Related]
4. Measures and models for causal inference in cross-sectional studies: arguments for the appropriateness of the prevalence odds ratio and related logistic regression.
Reichenheim ME; Coutinho ES
BMC Med Res Methodol; 2010 Jul; 10():66. PubMed ID: 20633293
[TBL] [Abstract][Full Text] [Related]
5. Prevalence odds ratio or prevalence ratio in the analysis of cross sectional data: what is to be done?
Thompson ML; Myers JE; Kriebel D
Occup Environ Med; 1998 Apr; 55(4):272-7. PubMed ID: 9624282
[TBL] [Abstract][Full Text] [Related]
6. Prevalence proportion ratios: estimation and hypothesis testing.
Skov T; Deddens J; Petersen MR; Endahl L
Int J Epidemiol; 1998 Feb; 27(1):91-5. PubMed ID: 9563700
[TBL] [Abstract][Full Text] [Related]
7. Odds Ratio or Prevalence Ratio? An Overview of Reported Statistical Methods and Appropriateness of Interpretations in Cross-sectional Studies with Dichotomous Outcomes in Veterinary Medicine.
Martinez BAF; Leotti VB; Silva GSE; Nunes LN; Machado G; Corbellini LG
Front Vet Sci; 2017; 4():193. PubMed ID: 29177157
[TBL] [Abstract][Full Text] [Related]
8. A comparison of two methods for estimating prevalence ratios.
Petersen MR; Deddens JA
BMC Med Res Methodol; 2008 Feb; 8():9. PubMed ID: 18307814
[TBL] [Abstract][Full Text] [Related]
9. Obtaining adjusted prevalence ratios from logistic regression models in cross-sectional studies.
Bastos LS; Oliveira Rde V; Velasque Lde S
Cad Saude Publica; 2015 Mar; 31(3):487-95. PubMed ID: 25859716
[TBL] [Abstract][Full Text] [Related]
10. A simple method for estimating relative risk using logistic regression.
Diaz-Quijano FA
BMC Med Res Methodol; 2012 Feb; 12():14. PubMed ID: 22335836
[TBL] [Abstract][Full Text] [Related]
11. [Overview of multivariate regression model analysis and application].
Yu SC; Qi X; Hu YH; Zheng WJ; Wang QQ; Yao HY
Zhonghua Yu Fang Yi Xue Za Zhi; 2019 Mar; 53(3):334-336. PubMed ID: 30841679
[TBL] [Abstract][Full Text] [Related]
12. Odds ratios from logistic, geometric, Poisson, and negative binomial regression models.
Sroka CJ; Nagaraja HN
BMC Med Res Methodol; 2018 Oct; 18(1):112. PubMed ID: 30342488
[TBL] [Abstract][Full Text] [Related]
13. Estimating the incidence rate ratio in cross-sectional studies using a simple alternative to logistic regression.
Martuzzi M; Elliott P
Ann Epidemiol; 1998 Jan; 8(1):52-5. PubMed ID: 9465994
[TBL] [Abstract][Full Text] [Related]
14. Different methods to calculate effect estimates in cross-sectional studies. A comparison between prevalence odds ratio and prevalence ratio.
Behrens T; Taeger D; Wellmann J; Keil U
Methods Inf Med; 2004; 43(5):505-9. PubMed ID: 15702210
[TBL] [Abstract][Full Text] [Related]
15. Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data.
Austin PC; Stryhn H; Leckie G; Merlo J
Stat Med; 2018 Feb; 37(4):572-589. PubMed ID: 29114926
[TBL] [Abstract][Full Text] [Related]
16. Comparing performance between log-binomial and robust Poisson regression models for estimating risk ratios under model misspecification.
Chen W; Qian L; Shi J; Franklin M
BMC Med Res Methodol; 2018 Jun; 18(1):63. PubMed ID: 29929477
[TBL] [Abstract][Full Text] [Related]
17. Methods for estimating prevalence ratios in cross-sectional studies.
Coutinho LM; Scazufca M; Menezes PR
Rev Saude Publica; 2008 Dec; 42(6):992-8. PubMed ID: 19009156
[TBL] [Abstract][Full Text] [Related]
18. Investigating the Source of a Disease Outbreak Based on Risk Estimation: A Simulation Study Comparing Risk Estimates Obtained From Logistic and Poisson Regression Applied to a Dichotomous Outcome.
Rojanaworarit C; Wong JJ
Ochsner J; 2019; 19(3):220-226. PubMed ID: 31528132
[No Abstract] [Full Text] [Related]
19. [Clinical research XXII. From clinical judgment to Cox proportional hazards model].
Pérez-Rodríguez M; Rivas-Ruiz R; Palacios-Cruz L; Talavera JO
Rev Med Inst Mex Seguro Soc; 2014; 52(4):430-5. PubMed ID: 25078746
[TBL] [Abstract][Full Text] [Related]
20. Cox proportional hazards models have more statistical power than logistic regression models in cross-sectional genetic association studies.
van der Net JB; Janssens AC; Eijkemans MJ; Kastelein JJ; Sijbrands EJ; Steyerberg EW
Eur J Hum Genet; 2008 Sep; 16(9):1111-6. PubMed ID: 18382476
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]