메뉴 건너뛰기




Volumn 7, Issue 1, 2011, Pages

Relative risk estimation in randomized controlled trials: A comparison of methods for independent observations

Author keywords

binary outcome; log binomial regression; randomized controlled trial; relative risk; simulation

Indexed keywords

ACCURACY; ARTICLE; BINOMIAL DISTRIBUTION; HUMAN; INDEPENDENT VARIABLE; INTERMETHOD COMPARISON; POWER ANALYSIS; RANDOMIZED CONTROLLED TRIAL (TOPIC); RISK FACTOR; SENSITIVITY ANALYSIS; SIMULATION;

EID: 79951486848     PISSN: 15574679     EISSN: None     Source Type: Journal    
DOI: 10.2202/1557-4679.1278     Document Type: Article
Times cited : (33)

References (32)
  • 2
    • 2942735430 scopus 로고    scopus 로고
    • Alternatives for logistic regression in cross-sectional studies: An empirical comparison of models that directly estimate the prevalence ratio
    • Barros, A. J. and Hirakata, V. N. (2003). Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Medical Research Methodology 3: 21.
    • (2003) BMC Medical Research Methodology , vol.3 , pp. 21
    • Barros, A.J.1    Hirakata, V.N.2
  • 4
    • 33644688570 scopus 로고    scopus 로고
    • Parameter estimation and goodness-of-fit in log binomial regression
    • DOI 10.1002/bimj.200410165
    • Blizzard, L. and Hosmer, D. W. (2006). Parameter estimation and goodness-of-fit in log b (Pubitemid 43331719)
    • (2006) Biometrical Journal , vol.48 , Issue.1 , pp. 5-22
    • Blizzard, L.1    Hosmer, D.W.2
  • 5
    • 7944234695 scopus 로고    scopus 로고
    • A randomized trial of the Fischer cone biopsy excisor and loop electrosurgical excision procedure
    • DOI 10.1097/01.AOG.0000139517.26003.fc
    • Boardman, L. A., Steinhoff, M. M., Shackelton, R., Weitzen, S. and Crowthers, L. (2004). A randomized trial of the Fischer cone biopsy excisor and loop electrosurgical excision procedure. Obstetrics and Gynecology 104(4):745-750. (Pubitemid 40458803)
    • (2004) Obstetrics and Gynecology , vol.104 , Issue.4 , pp. 745-750
    • Boardman, L.A.1    Steinhoff, M.M.2    Shackelton, R.3    Weitzen, S.4    Crowthers, L.5
  • 6
    • 0034657861 scopus 로고    scopus 로고
    • Bootstrap confidence intervals: When, which, what? A practical guide for medical statisticians
    • DOI 10.1002/(SICI)1097-0258(20000515) 19:9<1141::AID-SIM479>3.0. CO;2-F
    • Carpenter, J. and Bithell, J. (2000). Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians. Statistics in Medicine 19(9): 1141-1164. (Pubitemid 30265928)
    • (2000) Statistics in Medicine , vol.19 , Issue.9 , pp. 1141-1164
    • Carpenter, J.1    Bithell, J.2
  • 7
    • 21644468954 scopus 로고    scopus 로고
    • Quasi-likelihood estimation for relative risk regression models
    • DOI 10.1093/biostatistics/kxh016
    • Carter, R. E., Lipsitz, S. R. and Tilley, B. C. (2005). Quasi-likelihood estimation for relative risk regression models. Biostatistics 6(1): 39-44. (Pubitemid 41240368)
    • (2005) Biostatistics , vol.6 , Issue.1 , pp. 39-44
    • Carter, R.E.1    Lipsitz, S.R.2    Tilley, B.C.3
  • 8
    • 68949111978 scopus 로고    scopus 로고
    • Methods for estimating adjusted risk ratios
    • Cummings, P. (2009). Methods for estimating adjusted risk ratios. Stata Journal 9(2): 175-196.
    • (2009) Stata Journal , vol.9 , Issue.2 , pp. 175-196
    • Cummings, P.1
  • 10
    • 0023257539 scopus 로고
    • Large sample confidence intervals for regression standardized risks, risk ratios, and risk differences
    • DOI 10.1016/0021-9681(87)90106-8
    • Flanders, W. D. and Rhodes, P. H. (1987). Large sample confidence intervals for regression standardized risks, risk ratios, and risk differences. Journal of Chronic Diseases 40(7): 697-704. (Pubitemid 17113476)
    • (1987) Journal of Chronic Diseases , vol.40 , Issue.7 , pp. 697-704
    • Flanders, W.D.1    Rhodes, P.H.2
  • 11
    • 77956891487 scopus 로고
    • Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates
    • Gail, M. H., Wieand, S. and Piantadosi, S. (1984). Biased estimates of treatment effect in randomized experiments with nonlinear regressions and omitted covariates. Biometrika 71(3): 431-444.
    • (1984) Biometrika , vol.71 , Issue.3 , pp. 431-444
    • Gail, M.H.1    Wieand, S.2    Piantadosi, S.3
  • 13
    • 0033566769 scopus 로고    scopus 로고
    • Statistical principles for clinical trials
    • ICH E9 Expert Working Group
    • ICH E9 Expert Working Group (1999). Statistical principles for clinical trials. Statistics in Medicine 18(15): 1905-1942.
    • (1999) Statistics in Medicine , vol.18 , Issue.15 , pp. 1905-1942
  • 14
    • 58349088984 scopus 로고    scopus 로고
    • What's the risk? A simple approach for estimating adjusted risk measures from nonlinear models including logistic regression
    • Kleinman, L. C. and Norton, E. C. (2009). What's the risk? A simple approach for estimating adjusted risk measures from nonlinear models including logistic regression. Health Services Research 44(1): 288-302.
    • (2009) Health Services Research , vol.44 , Issue.1 , pp. 288-302
    • Kleinman, L.C.1    Norton, E.C.2
  • 15
    • 0028348329 scopus 로고
    • Odds ratio or relative risk for cross-sectional data? [1]
    • Lee, J. (1994). Odds ratio or relative risk for cross-sectional data. International Journal of Epidemiology 23(1): 201-203. (Pubitemid 24088622)
    • (1994) International Journal of Epidemiology , vol.23 , Issue.1 , pp. 201-203
    • Lee, J.1
  • 16
    • 34547659742 scopus 로고    scopus 로고
    • Relative risks and confidence intervals were easily computed indirectly from multivariable logistic regression
    • DOI 10.1016/j.jclinepi.2006.12.001, PII S0895435606004690
    • Localio, A. R., Margolis, D. J. and Berlin, J. A. (2007). Relative risks and confidence intervals were easily computed indirectly from multivariable logistic regression. Journal of Clinical Epidemiology 60(9): 874-882. (Pubitemid 47208538)
    • (2007) Journal of Clinical Epidemiology , vol.60 , Issue.9 , pp. 874-882
    • Localio, A.R.1    Margolis, D.J.2    Berlin, J.A.3
  • 19
    • 0037541565 scopus 로고    scopus 로고
    • Estimating the relative risk in cohort studies and clinical trials of common outcomes
    • DOI 10.1093/aje/kwg074
    • McNutt, L. A., Wu, C. T., Xue, X. N. and Hafner, J. P. (2003). Estimating the relative risk in cohort studies and clinical trials of common outcomes. American Journal of Epidemiology 157(10): 940-943. (Pubitemid 36555054)
    • (2003) American Journal of Epidemiology , vol.157 , Issue.10 , pp. 940-943
    • McNutt, L.-A.1    Wu, C.2    Xue, X.3    Hafner, J.P.4
  • 21
    • 68249084602 scopus 로고    scopus 로고
    • Complementary log-log regression for the estimation of covariate-adjusted prevalence ratios in the analysis of data from cross-sectional studies
    • Penman, A. D. and Johnson, W. D. (2009). Complementary log-log regression for the estimation of covariate-adjusted prevalence ratios in the analysis of data from cross-sectional studies. Biometrical Journal 51(3): 433-442.
    • (2009) Biometrical Journal , vol.51 , Issue.3 , pp. 433-442
    • Penman, A.D.1    Johnson, W.D.2
  • 22
    • 41949133657 scopus 로고    scopus 로고
    • A comparison of two methods for estimating prevalence ratios
    • Petersen, M. R. and Deddens, J. A. (2008). A comparison of two methods for estimating prevalence ratios. BMC Medical Research Methodology 8: 9.
    • (2008) BMC Medical Research Methodology , vol.8 , pp. 9
    • Petersen, M.R.1    Deddens, J.A.2
  • 23
    • 0036740882 scopus 로고    scopus 로고
    • Odds ratio, relative risk, absolute risk reduction, and the number needed to treat-Which of these should we use?
    • Schechtman, E. (2002). Odds ratio, relative risk, absolute risk reduction, and the number needed to treat-Which of these should we use? Value in Health 5(5): 431-436.
    • (2002) Value in Health , vol.5 , Issue.5 , pp. 431-436
    • Schechtman, E.1
  • 25
    • 0028018289 scopus 로고
    • Clinically useful measures of effect in binary analyses of randomized trials
    • DOI 10.1016/0895-4356(94)90191-0
    • Sinclair, J. C. and Bracken, M. B. (1994). Clinically useful measures of effect in binary analyses of randomized trials. Journal of Clinical Epidemiology 47(8): 881-889. (Pubitemid 24268892)
    • (1994) Journal of Clinical Epidemiology , vol.47 , Issue.8 , pp. 881-889
    • Sinclair, J.C.1    Bracken, M.B.2
  • 26
    • 0031910123 scopus 로고    scopus 로고
    • Prevalence proportion ratios: Estimation and hypothesis testing
    • DOI 10.1093/ije/27.1.91
    • Skov, T., Deddens, J., Petersen, M. R. and Endahl, L. (1998). Prevalence proportion ratios: estimation and hypothesis testing. International Journal of Epidemiology 27(1): 91-95. (Pubitemid 28140509)
    • (1998) International Journal of Epidemiology , vol.27 , Issue.1 , pp. 91-95
    • Skov, T.1    Deddens, J.2    Petersen, M.R.3    Endahl, L.4
  • 27
    • 24144458327 scopus 로고    scopus 로고
    • Easy SAS calculations for risk or prevalence ratios and differences
    • DOI 10.1093/aje/kwi188, Correction of Anemia and Treatment with Dialysis: Novel Therapeutic Modalities in Congestive Heart Failure
    • Spiegelman, D. and Hertzmark, E. (2005). Easy SAS calculations for risk or prevalence ratios and differences. American Journal of Epidemiology 162(3): 199-200. (Pubitemid 41373523)
    • (2005) American Journal of Epidemiology , vol.162 , Issue.3 , pp. 199-200
    • Spiegelman, D.1    Hertzmark, E.2
  • 29
    • 0022629577 scopus 로고
    • Binomial regression in GLIM: Estimating risk ratios and risk differences
    • Wacholder, S. (1986). Binomial regression in GLIM: estimating risk ratios and risk differences. American Journal of Epidemiology 123(1): 174-184. (Pubitemid 16189710)
    • (1986) American Journal of Epidemiology , vol.123 , Issue.1 , pp. 174-184
    • Wacholder, S.1
  • 30
    • 0033825852 scopus 로고    scopus 로고
    • Choice of effect measure for epidemiological data
    • Walter, S. D. (2000). Choice of effect measure for epidemiological data. Journal of Clinical Epidemiology 53(9): 931-939.
    • (2000) Journal of Clinical Epidemiology , vol.53 , Issue.9 , pp. 931-939
    • Walter, S.D.1
  • 31
    • 40849137615 scopus 로고    scopus 로고
    • Estimating relative risks for common outcome using PROC NLP
    • Yu, B. B. and Wang, Z. Q. (2008). Estimating relative risks for common outcome using PROC NLP. Computer Methods and Programs in Biomedicine 90(2): 179-186.
    • (2008) Computer Methods and Programs in Biomedicine , vol.90 , Issue.2 , pp. 179-186
    • Yu, B.B.1    Wang, Z.Q.2
  • 32
    • 1642420994 scopus 로고    scopus 로고
    • A modified Poisson regression approach to prospective studies with binary data
    • Zou, G. Y. (2004). A modified Poisson regression approach to prospective studies with binary data. American Journal of Epidemiology 159(7): 702-706.
    • (2004) American Journal of Epidemiology , vol.159 , Issue.7 , pp. 702-706
    • Zou, G.Y.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.