Quantifying Treatment Effects When Flexibly Modeling Individual Change in a Nonlinear Mixed Effects Model

2021 ◽  
Vol 9 (2) ◽  
pp. 221-241
Author(s):  
Robert J. Gallop ◽  
Sona Dimidjian ◽  
David C. Atkins ◽  
Vito Muggeo
Keyword(s):  
Treatment Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Individual Change ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Model

Modeling response curves and testing treatment effects in repeated measures experiments: a multilevel nonlinear mixed-effects model approach

2005 ◽  
Vol 35 (1) ◽  
pp. 122-132 ◽  
Author(s):  
Dehai Zhao ◽  
Machelle Wilson ◽  
Bruce E Borders
Keyword(s):  
Repeated Measures ◽  
Growth Response ◽  
Treatment Effects ◽  
Model Building ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
General Strategy ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Model ◽  
Vegetation Control

A multilevel nonlinear mixed-effects modeling approach is used to model loblolly pine (Pinus taeda L.) stand volume growth in conjunction with four silvicultural treatments. Comparisons of treatment effects over time are integrated with the model-building process. Three-level random effects are introduced into a modified Richards growth model. Within-plot heterogeneity and correlation still occur, which are described by the exponential variance function and a first-order autoregressive model. The combination of complete vegetation control with fertilization results in the largest growth response; annual fertilization has the next largest growth response, with the exception that at very early stages the response is lower than that of vegetation control only; the control has the lowest growth response. The advantages of the multilevel nonlinear mixed effects model include its ability to handle unbalanced and incomplete repeated measures data, its flexibility to model multiple sources of heterogeneity and complex patterns of correlation, and its higher power to make treatment comparisons. We address in detail a general strategy of multilevel nonlinear mixed effects model building.

scholarly journals A flexible nonlinear mixed effects model for HIV viral load rebound after treatment interruption

2020 ◽  
Vol 39 (15) ◽  
pp. 2051-2066 ◽  
Author(s):  
Rui Wang ◽  
Ante Bing ◽  
Cathy Wang ◽  
Yuchen Hu ◽  
Ronald J. Bosch ◽  
...  
Keyword(s):  
Viral Load ◽  
Treatment Interruption ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Nonlinear Mixed Effects ◽  
Hiv Viral Load ◽  
Nonlinear Mixed Effects Model ◽  
Viral Load Rebound

scholarly journals Retrospective analysis of chronic hepatitis C in untreated patients with nonlinear mixed effects model

2008 ◽  
Vol 01 (02) ◽  
pp. 85-90
Author(s):  
Jian Huang ◽  
Kathleen O’Sullivan ◽  
John Levis ◽  
Elizabeth Kenny-Walsh ◽  
Orla Crosbie ◽  
...  
Keyword(s):  
Chronic Hepatitis ◽  
Hepatitis C ◽  
Retrospective Analysis ◽  
Chronic Hepatitis C ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Model
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