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Multiple‐bias modelling for analysis of observational data

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Cited by:

  1. Lawrence C. McCandless & Sylvia Richardson & Nicky Best, 2012. "Adjustment for Missing Confounders Using External Validation Data and Propensity Scores," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 40-51, March.
  2. Julian P. T. Higgins & Simon G. Thompson & David J. Spiegelhalter, 2009. "A re‐evaluation of random‐effects meta‐analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 137-159, January.
  3. Desiree C Wilks & Stephen J Sharp & Ulf Ekelund & Simon G Thompson & Adrian P Mander & Rebecca M Turner & Susan A Jebb & Anna Karin Lindroos, 2011. "Objectively Measured Physical Activity and Fat Mass in Children: A Bias-Adjusted Meta-Analysis of Prospective Studies," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-8, February.
  4. McCandless Lawrence C., 2012. "Meta-Analysis of Observational Studies with Unmeasured Confounders," The International Journal of Biostatistics, De Gruyter, vol. 8(2), pages 1-31, January.
  5. Jiang, Zhichao & Ding, Peng, 2017. "The directions of selection bias," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 104-109.
  6. N. J. Welton & A. E. Ades & J. B. Carlin & D. G. Altman & J. A. C. Sterne, 2009. "Models for potentially biased evidence in meta‐analysis using empirically based priors," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 119-136, January.
  7. N. J. Cooper & A. J. Sutton & A. E. Ades & S. Paisley & D. R. Jones, 2007. "Use of evidence in economic decision models: practical issues and methodological challenges," Health Economics, John Wiley & Sons, Ltd., vol. 16(12), pages 1277-1286.
  8. Maria Gheorghe & Susan Picavet & Monique Verschuren & Werner B. F. Brouwer & Pieter H. M. Baal, 2017. "Health losses at the end of life: a Bayesian mixed beta regression approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 723-749, June.
  9. S. Dias & N. J. Welton & V. C. C. Marinho & G. Salanti & J. P. T. Higgins & A. E. Ades, 2010. "Estimation and adjustment of bias in randomized evidence by using mixed treatment comparison meta‐analysis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(3), pages 613-629, July.
  10. Martin Ladouceur & Elham Rahme & Christian A. Pineau & Lawrence Joseph, 2007. "Robustness of Prevalence Estimates Derived from Misclassified Data from Administrative Databases," Biometrics, The International Biometric Society, vol. 63(1), pages 272-279, March.
  11. P. Gustafson & L. C. McCandless & A. R. Levy & S. Richardson, 2010. "Simplified Bayesian Sensitivity Analysis for Mismeasured and Unobserved Confounders," Biometrics, The International Biometric Society, vol. 66(4), pages 1129-1137, December.
  12. Kaatje Bollaerts & Vivek Shinde & Gaël Dos Santos & Germano Ferreira & Vincent Bauchau & Catherine Cohet & Thomas Verstraeten, 2016. "Application of Probabilistic Multiple-Bias Analyses to a Cohort- and a Case-Control Study on the Association between Pandemrix™and Narcolepsy," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-14, February.
  13. Douglas E. Schaubel & Guanghui Wei, 2011. "Double Inverse-Weighted Estimation of Cumulative Treatment Effects Under Nonproportional Hazards and Dependent Censoring," Biometrics, The International Biometric Society, vol. 67(1), pages 29-38, March.
  14. Engsted, Tom & Schneider, Jesper W., 2023. "Non-Experimental Data, Hypothesis Testing, and the Likelihood Principle: A Social Science Perspective," SocArXiv nztk8, Center for Open Science.
  15. A. M. Presanis & D. De Angelis & D. J. Spiegelhalter & S. Seaman & A. Goubar & A. E. Ades, 2008. "Conflicting evidence in a Bayesian synthesis of surveillance data to estimate human immunodeficiency virus prevalence," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 915-937, October.
  16. Rebecca M Turner & Myfanwy Lloyd-Jones & Dilly O C Anumba & Gordon C S Smith & David J Spiegelhalter & Hazel Squires & John W Stevens & Michael J Sweeting & Stanislaw J Urbaniak & Robert Webster & Sim, 2012. "Routine Antenatal Anti-D Prophylaxis in Women Who Are Rh(D) Negative: Meta-Analyses Adjusted for Differences in Study Design and Quality," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-10, February.
  17. Carlos Díaz-Venegas, 2014. "Identifying the Confounders of Marginalization and Mortality in Mexico, 2003–2007," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 118(2), pages 851-875, September.
  18. Ximena P. Vergara & Heidi J. Fischer & Michael Yost & Michael Silva & David A. Lombardi & Leeka Kheifets, 2015. "Job Exposure Matrix for Electric Shock Risks with Their Uncertainties," IJERPH, MDPI, vol. 12(4), pages 1-14, April.
  19. K. M. Rhodes & J. Savović & R. Elbers & H. E. Jones & J. P. T. Higgins & J. A. C. Sterne & N. J. Welton & R. M. Turner, 2020. "Adjusting trial results for biases in meta‐analysis: combining data‐based evidence on bias with detailed trial assessment," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 193-209, January.
  20. Nuoo‐Ting Molitor & Nicky Best & Chris Jackson & Sylvia Richardson, 2009. "Using Bayesian graphical models to model biases in observational studies and to combine multiple sources of data: application to low birth weight and water disinfection by‐products," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 615-637, June.
  21. Qi Zhou & Yoo-Mi Chin & James D. Stamey & Joon Jin Song, 2020. "Bayesian sensitivity analysis to unmeasured confounding for misclassified data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 577-596, December.
  22. A. Goubar & A. E. Ades & D. De Angelis & C. A. McGarrigle & C. H. Mercer & P. A. Tookey & K. Fenton & O. N. Gill, 2008. "Estimates of human immunodeficiency virus prevalence and proportion diagnosed based on Bayesian multiparameter synthesis of surveillance data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(3), pages 541-580, June.
  23. Leeka Kheifets & Jack D. Sahl & Riti Shimkhada & Mike H. Repacholi, 2005. "Developing Policy in the Face of Scientific Uncertainty: Interpreting 0.3 μT or 0.4 μT Cutpoints from EMF Epidemiologic Studies," Risk Analysis, John Wiley & Sons, vol. 25(4), pages 927-935, August.
  24. Xavier de Luna & Mathias Lundin, 2014. "Sensitivity analysis of the unconfoundedness assumption with an application to an evaluation of college choice effects on earnings," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1767-1784, August.
  25. Paul Gustafson, 2007. "Measurement error modelling with an approximate instrumental variable," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 69(5), pages 797-815, November.
  26. H. Lu & P. Yin & R.X. Yue & J.Q. Shi, 2015. "Robust confidence intervals for trend estimation in meta-analysis with publication bias," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(12), pages 2715-2733, December.
  27. Paul Gustafson, 2006. "Sample size implications when biases are modelled rather than ignored," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(4), pages 865-881, October.
  28. A. E. Ades & A. J. Sutton, 2006. "Multiparameter evidence synthesis in epidemiology and medical decision‐making: current approaches," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(1), pages 5-35, January.
  29. Andrew Gelman & Christian Hennig, 2017. "Beyond subjective and objective in statistics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(4), pages 967-1033, October.
  30. Brian H. MacGillivray, 2019. "Null Hypothesis Testing ≠ Scientific Inference: A Critique of the Shaky Premise at the Heart of the Science and Values Debate, and a Defense of Value‐Neutral Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 39(7), pages 1520-1532, July.
  31. Laura L. F. Scott & George Maldonado, 2015. "Quantifying and Adjusting for Disease Misclassification Due to Loss to Follow-Up in Historical Cohort Mortality Studies," IJERPH, MDPI, vol. 12(10), pages 1-13, October.
  32. de Luna, Xavier & Lundin, Mathias, 2009. "Sensitivity analysis of the unconfoundedness assumption in observational studies," Working Paper Series 2009:12, IFAU - Institute for Evaluation of Labour Market and Education Policy.
  33. Rebecca M. Turner & David J. Spiegelhalter & Gordon C. S. Smith & Simon G. Thompson, 2009. "Bias modelling in evidence synthesis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 21-47, January.
  34. Graham Scotland & Stirling Bryan, 2017. "Why Do Health Economists Promote Technology Adoption Rather Than the Search for Efficiency? A Proposal for a Change in Our Approach to Economic Evaluation in Health Care," Medical Decision Making, , vol. 37(2), pages 139-147, February.
  35. Leah Comment & Brent A. Coull & Corwin Zigler & Linda Valeri, 2022. "Bayesian data fusion: Probabilistic sensitivity analysis for unmeasured confounding using informative priors based on secondary data," Biometrics, The International Biometric Society, vol. 78(2), pages 730-741, June.
  36. Paul Gustafson & Lawrence C. McCandless, 2010. "Probabilistic Approaches to Better Quantifying the Results of Epidemiologic Studies," IJERPH, MDPI, vol. 7(4), pages 1-20, April.
  37. Enrique A. Navarro-Camba & Jaume Segura-García & Claudio Gomez-Perretta, 2018. "Exposure to 50 Hz Magnetic Fields in Homes and Areas Surrounding Urban Transformer Stations in Silla (Spain): Environmental Impact Assessment," Sustainability, MDPI, vol. 10(8), pages 1-11, July.
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