Ranstam Review DataBase (RR.db)

References in category "parameters"

  1. Barros AJD, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Method 2003, 3:21 [PubMed] [Google]

  2. Coutinho LMS, Scazufca M, Menezes PR. Methods for estimating prevalence ratios in cross-sectional studies. Rev Saúde Pública 2008;42:1-6. [PubMed] [Google]

  3. Davies HTO. When can odds ratios mislead? BMJ 1998;316:989. [PubMed] [Google]

  4. Dignam JJ, Zhang Q, Kocherginsky MN. The Use and Interpretion of Competing Risks Regression Models. Clin Cancer Res 2012;18:2301–2308. [PubMed] [Google]

  5. Graubard BI, Korn EL. Inference for Superpopulation Parameters Using Sample Surveys. Statistical Science 2002;17:73–96. [PubMed] [Google]

  6. Greenland S, Schlesselman JJ, Criqui, MH. The fallacy of employing standardized regression coefficients and correlations as measures of effect. Am J Epidemiol. 1986;123:203–208. [PubMed] [Google]

  7. Knol MJ, Duijnhoven RG, Grobbee DE, Moons KGM, Groenwold RHH. Potential Misinterpretation of Treatment Effects Due to Use of Odds Ratios and Logistic Regression in Randomized Controlled Trials. PLoS One. 2011; 6(6): e21248. [PubMed] [Google]

  8. McNutt L-A, Wu C, Xue X, Hafner JP. Estimating the Relative Risk in Cohort Studies and Clinical Trials of Common Outcomes. Am J Epidemiol 2003;157:940–943. [PubMed] [Google]

  9. Sayers A, Evans JT, Whitehouse MR, Blom AW. Are competing risks models appropriate to describe implant failure? Acta Orthop 2018;89:256–258. [PubMed] [Google]

  10. Tajeu GS, Sen B, Allison DB, Menachemi N. Misuse of odds ration in obesity literature: an empirical analysis of published studies. 2012; 20:1726-1731. [PubMed] [Google]

  11. Zhang J, Yu KF. What’s the Relative Risk? A Method of Correcting the Odds Ratio in Cohort Studies of Common Outcomes. JAMA 1998;280:1690-1691. [PubMed] [Google]


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