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.