Methods to apply probabilistic bias analysis to summary estimates of association

Bias analysis methods are developed for application to 2 × 2 tables, which may be crude or stratified data. Methods for application to associations adjusted for multiple covariates, such as associations from regression modeling, are rarely seen. We have developed probabilistic methods to evaluate bias from disease misclassification or an unmeasured confounder that can be applied to adjusted estimates of association.

[1]  B. Jilma,et al.  Effects of pantoprazole and esomeprazole on platelet inhibition by clopidogrel. , 2009, American heart journal.

[2]  Timothy L. Lash,et al.  Applying Quantitative Bias Analysis to Epidemiologic Data , 2009, Statistics for Biology and Health.

[3]  Roger Logan,et al.  Estimation and Inference for Logistic Regression with Covariate Misclassification and Measurement Error in Main Study/Validation Study Designs , 2000 .

[4]  Takashi Yanagawa,et al.  Case-control studies: Assessing the effect of a confounding factor , 1984 .

[5]  I. Bross,et al.  Pertinency of an extraneous variable. , 1967, Journal of chronic diseases.

[6]  P. Levy.  Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments , 2004 .

[7]  D. Spiegelman,et al.  Corrected score estimation in the proportional hazards model with misclassified discrete covariates , 2008, Statistics in medicine.

[8]  I. Bross.  Misclassification in 2 X 2 Tables , 1954 .

[9]  I. Bross.  Spurious effects from an extraneous variable. , 1966, Journal of chronic diseases.

[10]  G Maldonado,et al.  Adjusting a relative-risk estimate for study imperfections , 2008, Journal of Epidemiology and Community Health.

[11]  R. Stern.  The mysteries of geographic variability in nonmelanoma skin cancer incidence. , 1999, Archives of dermatology.

[12]  D. Holmes,et al.  Effect of smoking status on the long-term outcome after successful percutaneous coronary revascularization. , 1997, The New England journal of medicine.

[13]  D Spiegelman,et al.  Matrix Methods for Estimating Odds Ratios with Misclassified Exposure Data: Extensions and Comparisons , 1999, Biometrics.

[14]  T. Lash,et al.  Using probabilistic corrections to account for abstractor agreement in medical record reviews. , 2007, American journal of epidemiology.

[15]  E. C. Hammond,et al.  Smoking and lung cancer: recent evidence and a discussion of some questions. , 1959, Journal of the National Cancer Institute.

[16]  Timothy L Lash,et al.  Semi-Automated Sensitivity Analysis to Assess Systematic Errors in Observational Data , 2003, Epidemiology.

[17]  Timothy L Lash,et al.  A method to automate probabilistic sensitivity analyses of misclassified binary variables. , 2005, International journal of epidemiology.

[18]  Sander Greenland,et al.  Bias Analysis , 2011, International Encyclopedia of Statistical Science.

[19]  W. Flanders,et al.  Indirect Assessment of Confounding: Graphic Description and Limits on Effect of Adjusting for Covariates , 1990, Epidemiology.

[20]  C. Dethlefsen,et al.  Do incident and new subsequent cases of non-melanoma skin cancer registered in a Danish prospective cohort study have different 10-year mortality? , 2007, Cancer detection and prevention.

[21]  H. Sørensen,et al.  Use of oral glucocorticoids and risk of skin cancer and non-Hodgkin's lymphoma: a population-based case–control study , 2008, British Journal of Cancer.