The NIST SP 800-22 test suite is the generally accepted standard for Random Number Generator (RNG) evaluation. However, applying default parameters leads to Type I errors (false rejections) due to approximation errors and parameter sensitivity inherent in Level-1 statistic computation. While prior studies have analyzed these error sources, a systematic methodology to optimize parameters at this fundamental stage remains absent. To address this, we propose a parameter optimization method that mitigates structural Type I errors in the Frequency, Cumulative Sums, and Non-overlapping Template Matching tests. Specifically, for the Frequency and Cumulative Sums tests, we derive analytical pass thresholds from the test formulas and align them with the statistically modeled maximum values of the observed statistics to identify a stable pass region <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(n)</i>. In contrast, for the Non-overlapping Template Matching test, we employ a parameter sweep based on sensitivity analysis to determine the optimal parameter set <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(n,N)</i>. This approach minimizes approximation errors and resolves the hypersensitivity to strict decision boundaries, while securing sufficient statistical margins. Verification using a 28 nm CSRO-based TRNG confirms that optimized parameters achieve a 100 % pass rate across all chips, significantly improving upon the 72 % minimum pass rate observed with default parameters. These results indicate that the proposed optimization effectively mitigates structural Type I errors without compromising test sensitivity, enabling the evaluation to strictly target actual deficiencies. Furthermore, the proposed method is generally applicable to varying hardware implementations, allowing researchers to derive optimal verification parameters tailored to their specific entropy characteristics.