To assess the quality of a test suite, one can rely on mutation testing, which computes whether the overall test cases are adequately exercising the covered lines. However, this high level of granularity may overshadow the quality of individual test methods. Thus, we propose an empirical study of high-quality test methods by mutation testing. We analyze over 18K test methods from popular software projects and show empirical evidence that high-quality test methods: (1) are slightly smaller; (2) have fewer modifications over time; (3) are less affected by critical test smells. Lastly, we present practical implications for researchers and practitioners.