The importance of exploring a potential integration among surveys has been acknowledged in order to enhance effectiveness and minimize expenses. In this work, we employ the alignment method to combine information from two different surveys for the estimation of complex statistics. The derivation of the alignment weights poses challenges in case of complex statistics due to their non-linear form. To overcome this, we propose to use a linearized variable associated with the complex statistic under consideration. Linearized variables have been widely used to derive variance estimates, thus allowing for the estimation of the variance of the combined complex statistics estimates. Simulations conducted show the effectiveness of the proposed approach, resulting to the reduction of the variance of the combined complex statistics estimates. Also, in some cases, the usage of the alignment weights derived using the linearized variable associated with a complex statistic, could result in a further reduction of the variance of the combined estimates.

翻译：为了提升效率并降低成本，探索调查之间潜在整合的重要性已得到广泛认可。本文采用对齐方法，将来自两项不同调查的信息相结合，以估计复杂统计量。由于复杂统计量的非线性形式，对齐权重的推导面临挑战。为解决这一问题，我们提出使用与待估计复杂统计量相关的线性化变量。线性化变量已被广泛用于推导方差估计，从而能够估计合并后复杂统计量估计的方差。模拟实验表明，所提方法有效降低了合并后复杂统计量估计的方差。此外，在某些情况下，使用与复杂统计量相关的线性化变量导出的对齐权重，能够进一步减小合并估计的方差。