<p>Multilevel functional data have arisen more commonly in recent years with the rapid development of big data and medical research. Analyzing this multilevel functional data can better demonstrate the dynamic changes and improve the predictive performance. In this paper, we propose a new component estimation method for the multilevel functional principal component model. This method first implements the functional principal component analysis on the transformed single-level functional data, then obtains the estimation of the principal components of the multilevel functional principal component model based on the relationship between the single-level and the multilevel principal component models, thus realizing the two-stage estimation of the generalized multilevel functional regression model. We also further consider Bayesian estimation based on the two-stage estimation. The results of both the simulation study and the empirical analysis on ADNI data validate the effectiveness of our proposed method.</p>