Recycled Two-Stage Estimation in Nonlinear Mixed Effects Regression Models

2019/02/03 by Ben Boukai, Benzion Boukai, Yue Zhang +2
Computer Science · Decision Sciences · Mathematics · #62F12 #62G09 #Advanced Statistical Process Monitoring #Bayesian Methods and Mixture Models #FOS: Mathematics #Primary 62J02 #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST) #math.ST #msc:62F12 #msc:62F40 #msc:62G09 #msc:62J02 #secondary 62F40 #stat.TH

paper · pdf · doi:10.48550/arxiv.1902.00917

36 pages including 15 Tables, 7 Figures with 4 Theorem and 11 Lemas

arxiv created 2019/02/03 · openalex publication_date 2019/02/03 · arxiv updated 2019/02/05 · openalex created_date 2022/07/29 · openalex updated_date 2026/07/28

Abstract

We consider a re-sampling scheme for estimation of the population parameters in the mixed effects nonlinear regression models of the type use for example in clinical pharmacokinetics, say. We provide an estimation procedure which \it recycles, via random weighting, the relevant two-stage parameters estimates to construct consistent estimates of the sampling distribution of the various estimates. We establish the asymptotic consistency and asymptotic normality of the resampled estimates and demonstrate the applicability of the \it recycling approach in a small simulation study and via example.

Citations

• Asymptotic Properties of Non-Linear Least Squares Estimators
• Nonlinear Mixed Effects Models for Repeated Measures Data
• Bootstrap Methods: Another Look at the Jackknife

Related

• Recycled Least Squares Estimation in Nonlinear Regression
• Nonlinear Mixed Effects Models for Repeated Measures Data
• Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
• Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications
• Design and Analysis Considerations for Causal Inference under Two-Phase Sampling in Observational Studies