Newton—Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
重复测量线性混合效应模型的 Newton–Raphson 与 EM 算法
We develop an efficient and effective implementation of the Newton—Raphson (NR) algorithm for estimating the parameters in mixed-effects models for repeated-measures data. We formulate the derivatives for both maximum likelihood and restricted maximum likelihood estimation and propose improvements to the algorithm discussed by Jennrich and Schlüchter (1986) to speed convergence and ensure a positive-definite covariance matrix for the random effects at each iteration. We use…