Research Summary Hambrick and Quigley's (2014) “CEO in context” (CiC) technique leads to a much larger CEO effect than traditional ANOVA or multilevel modeling. We replicate H&Q's study, apply their CiC technique to a much more comprehensive U.S. sample, and assess the sensitivity of the model findings to variations in method and data. We generally confirm H&Q's finding of a high CEO effect, but find a smaller industry effect and a larger firm effect in our much larger sample. Applying the CiC technique with adjusted R2s has only a moderate impact on year, industry, and firm effects, but markedly reduces the CEO effect. We also document that CiC model findings are sensitive to sample characteristics, namely firm size and CEO tenure. Managerial Summary Hambrick and Quigley (2014) introduced a new method to analyze the influence of CEOs on firm performance. The study's empirical analysis focused on large U.S. firms. We replicate the original study and extend it to a much larger, comprehensive sample of U.S. firms that is composed of 33,996 firm‐year observations, compared to 4,866 firm‐years in the original study. Controlling for the number of variables used in the estimations, the model attributes about a third of the total variance of firm performance (ROA) to the CEO. Further analyses show that the model findings differ for firms of different size and CEO tenure; the larger the firms and the longer the CEO tenures, the smaller tends to be the percentage of variance explained by the CEO.