ArticlePsychometrika2016
Fitting Nonlinear Ordinary Differential Equation Models with Random Effects and Unknown Initial Conditions Using the Stochastic Approximation Expectation-Maximization (SAEM) Algorithm.
Article in Psychometrika, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Whole Person Recovery from Substance Use Disorder: A Call for Research Examining a Dynamic Behavioral Ecological Model of Contexts Supportive of Recovery.Addiction research & theory · 2025Article
- Unsupervised Model Construction in Continuous-Time.Structural equation modeling : a multidisciplinary journal · 2025Article
- What ergodicity means for you.Developmental cognitive neuroscience · 2024Review
- Estimation of nonlinear mixed-effects continuous-time models using the continuous-discrete extended Kalman filter.The British journal of mathematical and statistical psychology · 2023Article
- Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework.Psychometrika · 2022Article
- Dynamic models of stress-smoking responses based on high-frequency sensor data.NPJ digital medicine · 2021Article
- Identifying Qualitative Between-Subject and Within-Subject Variability: A Method for Clustering Regime-Switching Dynamics.Frontiers in psychology · 2020Article
- Zero-Inflated Regime-Switching Stochastic Differential Equation Models for Highly Unbalanced Multivariate, Multi-Subject Time-Series Data.Psychometrika · 2019Article
- Representing Sudden Shifts in Intensive Dyadic Interaction Data Using Differential Equation Models with Regime Switching.Psychometrika · 2018Article
- Bayesian Analysis of Ambulatory Blood Pressure Dynamics with Application to Irregularly Spaced Sparse Data.The annals of applied statistics · 2015Article
- Practical Tools and Guidelines for Exploring and Fitting Linear and Nonlinear Dynamical Systems Models.Multivariate behavioral researchArticle
- A Comparison of Two-Stage Approaches for Fitting Nonlinear Ordinary Differential Equation Models with Mixed Effects.Multivariate behavioral researchArticle
- Fitting Bayesian Stochastic Differential Equation Models with Mixed Effects through a Filtering Approach.Multivariate behavioral researchArticle
- Multilevel Latent Differential Structural Equation Model with Short Time Series and Time-Varying Covariates: A Comparison of Frequentist and Bayesian Estimators.Multivariate behavioral researchArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The past decade has evidenced the increased prevalence of irregularly spaced longitudinal data in social sciences. Clearly lacking, however, are modeling tools that allow researchers to fit dynamic models to irregularly spaced data, particularly data that show nonlinearity and heterogeneity in dynamical structures. We consider the issue of fitting multivariate nonlinear differential equation models with random effects and unknown initial conditions to irregularly spaced data. A stochastic approximation expectation-maximization algorithm is proposed and its performance is evaluated using a benchmark nonlinear dynamical systems model, namely, the Van der Pol oscillator equations. The empirical utility of the proposed technique is illustrated using a set of 24-h ambulatory cardiovascular data from 168 men and women. Pertinent methodological challenges and unresolved issues are discussed.
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