A main challenge in molecular diagnostic research is to accurately evaluate the performance of a new nucleic acid amplification test when the reference standard is imperfect. Several approaches, such as discrepant analysis, composite reference standard (CRS) method, or latent class analysis (LCA), are commonly applied for this purpose by combining multiple imperfect (reference) test results. In discrepant analysis or LCA, test results from the new assay are often involved in the construction of a new pseudo-reference standard, which results in the potential risk of overestimating the parameters of interest. On the contrary, the CRS methods only combine the results of reference tests, which is more preferable in practice. In this article, we study the properties of two extreme CRS methods, i.e., combining multiple reference test results by the "any positive" rule or by the "all-positive" rule, and propose a new approach "dual composite reference standards (dCRS)" based on these two extreme methods to reduce the biases of the estimates. Simulations are performed for various scenarios and the proposed approach is applied to two real datasets. The results demonstrate that our approach outperforms other commonly used approaches and therefore is recommended for future applications.