Abstract
OBJECTIVES: Model specification-what adjusting variables are analytically modeled-may influence results of observational associations. We present a standardized approach to quantify the variability of results obtained with choices of adjustments called the "vibration of effects" (VoE). STUDY DESIGN AND SETTING: We estimated the VoE for 417 clinical, environmental, and physiological variables in association with all-cause mortality using National Health and Nutrition Examination Survey data. We selected 13 variables as adjustment covariates and computed 8,192 Cox models for each of 417 variables' associations with all-cause mortality. RESULTS: We present the VoE by assessing the variance of the effect size and in the -log10(P-value) obtained by different combinations of adjustments. We present whether there are multimodality patterns in effect sizes and P-values and the trajectory of results with increasing adjustments. For 31% of the 417 variables, we observed a Janus effect, with the effect being in opposite direction in the 99th versus the 1st percentile of analyses. For example, the vitamin E variant α-tocopherol had a VoE that indicated higher and lower risk for mortality. CONCLUSION: Estimating VoE offers empirical estimates of associations are under different model specifications. When VoE is large, claims for observational associations should be very cautious.