Reader's guide to critical appraisal of cohort studies: 2. Assessing potential for confounding

By M. Mamdani, K. Sykora, Ping Li, Sharon-Lise T. Normand, D. Streiner, Peter C. Austin, P. Rochon, G. Anderson. British medical journal, 2005

626 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies (2015, background): “While there is no consensus as to what value of a standardized difference can be taken to indicate the presence of meaningful confounding, some authors have suggested that a standardized difference in excess of 10% may be indicative of meaningful imbalance in a covariates between treated and control”
Long-term analgesic use after low-risk surgery: a retrospective cohort study. (2012, neutral): “10 is generally considered to indicate a meaningful difference.(14) We used multivariate logistic regression to examine the association between analgesic initiation after short-stay surgery and long-term analgesic use.”