Open AccessThe change in estimate method for selecting confounders: A simulation study
Author(s) -
Denis Talbot,
Awa Diop,
Mathilde Lavigne-Robichaud,
Chantal Brisson
Publication year - 2021
Publication title -
statistical methods in medical research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.952
H-Index - 85
eISSN - 1477-0334
pISSN - 0962-2802
DOI - 10.1177/09622802211034219
Subject(s) - confounding , statistics , confidence interval , estimator , standard error , computer science , econometrics , medicine , mathematics
Background The change in estimate is a popular approach for selecting confounders in epidemiology. It is recommended in epidemiologic textbooks and articles over significance test of coefficients, but concerns have been raised concerning its validity. Few simulation studies have been conducted to investigate its performance.Methods An extensive simulation study was realized to compare different implementations of the change in estimate method. The implementations were also compared when estimating the association of body mass index with diastolic blood pressure in the PROspective Québec Study on Work and Health.Results All methods were susceptible to introduce important bias and to produce confidence intervals that included the true effect much less often than expected in at least some scenarios. Overall mixed results were obtained regarding the accuracy of estimators, as measured by the mean squared error. No implementation adequately differentiated confounders from non-confounders. In the real data analysis, none of the implementation decreased the estimated standard error.Conclusion Based on these results, it is questionable whether change in estimate methods are beneficial in general, considering their low ability to improve the precision of estimates without introducing bias and inability to yield valid confidence intervals or to identify true confounders.