Ranstam Review DataBase (RR.db)

Templates for phenomenon "confounding tests"

  1. Multivariable modeling is performed using factors with significant associations in univariable analysis. Developing a statistical model for effect estimation can, however, not be performed on the basis of statistical significance because p-values are measures of statistical precison and the model development should be made with respect to validity. The inclusion of variables needs instead to be based on assumptions regarding cause and effect, see e.g. Shrier I, Platt RW. Reducing bias through directed acyclic graphs. BMC Med Res Methodol 2008;8:70. Please provide a rationale for the included covariates in terms of cause-effect relationships. For the presentation of results, see Westreich D, Greenland S. The table 2 fallacy: presenting and interpreting confounder and modifier coefficients. Am J Epidemiol 2013;177:292-298.