A two-stage mixed-effects model approach for gene-set analyses in candidate gene studies

2011 ◽  
Vol 31 (11-12) ◽  
pp. 1190-1202 ◽  
Author(s):  
Roula Tsonaka ◽  
Annette H. M. van der Helm-van Mil ◽  
Jeanine J. Houwing-Duistermaat
Keyword(s):  
Candidate Gene ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Two Stage ◽  
Gene Set ◽  
Candidate Gene Studies ◽  
Model Approach

scholarly journals A mixed-effects model approach for estimating the distribution of usual intake of nutrients: The NCI method

2010 ◽  
Vol 29 (27) ◽  
pp. 2857-2868 ◽  
Author(s):  
Janet A. Tooze ◽  
Victor Kipnis ◽  
Dennis W. Buckman ◽  
Raymond J. Carroll ◽  
Laurence S. Freedman ◽  
...  
Keyword(s):  
Mixed Effects ◽  
Mixed Effects Model ◽  
Usual Intake ◽  
Model Approach

scholarly journals A beta‐binomial mixed‐effects model approach for analysing longitudinal discrete and bounded outcomes

2018 ◽  
Vol 61 (3) ◽  
pp. 600-615 ◽  
Author(s):  
Josu Najera‐Zuloaga ◽  
Dae‐Jin Lee ◽  
Inmaculada Arostegui
Keyword(s):  
Mixed Effects ◽  
Mixed Effects Model ◽  
Model Approach

scholarly journals Comparison of Fixed- and Mixed-effects Approaches to Taper Modeling for Scots Pine in West Poland

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 975 ◽  
Author(s):  
Karol Bronisz ◽  
Michał Zasada
Keyword(s):  
Random Effects ◽  
Scots Pine ◽  
Fixed Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Fixed Effects Model ◽  
Validation Data ◽  
Data Set ◽  
Taper Model ◽  
Model Approach

Diameter measurements along the stem, which are the basis for taper models, usually have a hierarchical structure. Mixed-effects models, where fixed and random effects are distinguished, are a possible solution for this type of data. However, in order to fully absorb the potential of this method, random effects prediction, which requires additional measurements (diameter along stem), is recommended. This article presents a comparison of various fitting methods (mixed- and fixed-effects model approaches) of the variable-exponent taper model created by Kozak for determining the outside bark diameter along the stem and predicting the tree volume of Scots pine trees in west Poland. During the analysis, it was assumed that no additional measured data were available for practical use; therefore, for the mixed-effects model approach, fixed effects prediction without random effects was applied. Both fitting strategies were compared based on modeling and an independent validation data set. The comparison of mixed- and fixed-effects fitting strategies for the diameter along the stem indicated that the taper model fitted using the mixed-effects model approach better fit the data. Moreover, the error rate for the total tree volume prediction for the independent data set was lower for the mixed-effects model solution than for the fixed-effects one.

scholarly journals Predicting pregnancy outcomes using longitudinal information: a penalized splines mixed-effects model approach

2017 ◽  
Vol 36 (13) ◽  
pp. 2120-2134 ◽  
Author(s):  
Rolando De la Cruz ◽  
Claudio Fuentes ◽  
Cristian Meza ◽  
Dae-Jin Lee ◽  
Ana Arribas-Gil
Keyword(s):  
Pregnancy Outcomes ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Penalized Splines ◽  
Model Approach

scholarly journals Predicting Budget Impact: A Mixed-Effects Model Approach

2017 ◽  
Vol 20 (9) ◽  
pp. A739
Author(s):  
JW Geenen ◽  
SV Belitser ◽  
RA Vreman ◽  
O Klungel ◽  
JA Raaijmakers ◽  
...  
Keyword(s):  
Budget Impact ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Model Approach

scholarly journals A Unified Mixed Effects Model for Gene Set Analysis of Time Course Microarray Experiments

2009 ◽  
Vol 8 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Lily Wang ◽  
Xi Chen ◽  
Russell D Wolfinger ◽  
Jeffrey L Franklin ◽  
Robert J Coffey ◽  
...  
Keyword(s):  
Time Course ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Gene Set Analysis ◽  
Microarray Experiments ◽  
Gene Set
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