Bayesian analysis for mixed-effects model defined by stochastic differential equations

The nonlinear mixed-effects model with stochastic differential equations （SDEs） is used to model the population pharmacokinetic （PPK） data that are extended from ordinary differential equations （ODEs） by adding a stochastic term to the state equation. Compared with the ODEs, the SDEs can model correlated residuals which are ubiquitous in actual pharmacokinetic problems. The Bayesian estimation is provided for nonlinear mixed-effects models based on stochastic differential equations. Combining the Gibbs and the Metropolis-Hastings algorithms, the population and individual parameter values are given through the parameter posterior predictive distributions. The analysis and simulation results show that the performance of the Bayesian estimation for mixed-effects SDEs model and analysis of population pharmacokinetic data is reliable. The results suggest that the proposed method is feasible for population pharmacokinetic data.

中国英语学习者主谓一致在线加工的研究——一项自定步速阅读实验

中国英语学习者能否达到类似母语者的在线自动加工主谓一致的能力,目前尚存争议。本研究采用自定步速阅读的研究范式,考察了两组英语水平相异的学习者被试在主谓相邻和不相邻条件下在线加工主谓(不)一致的反应时,同时考察被试的语言水平、工作记忆容量和其反应时的相关性。结果表明:1)两组学习者被试在两种条件下,都没有达到类似母语者的自动加工能力;2)在主谓相邻条件下,水平较高的学习者被试和水平较低的学习者被试的反应时存在显著差异;3)在主谓不相邻的条件下,学习者的工作记忆容量和其反应时呈显著相关。研究结果验证"形态一致性假设"和ACT自动性理论框架,对当前的外语教学具有一定的启发意义。