On confidence intervals for the among-group variance in the one-way random effects model with unequal error variances

2005 ◽  
Vol 127 (1-2) ◽  
pp. 157-177 ◽  
Author(s):  
Joachim Hartung ◽  
Guido Knapp
Keyword(s):  
Confidence Intervals ◽  
Random Effects ◽  
Random Effects Model ◽  
The One

scholarly journals On Jones et al.’s Method for Assessing Limits of Agreement with the Mean for Multiple Observers

2020 ◽  
Author(s):  
Heidi S. Christensen ◽  
Jens Borgbjerg ◽  
Lars Børty ◽  
Martin Bøgsted
Keyword(s):  
Confidence Intervals ◽  
Random Effects ◽  
Tumour Size ◽  
Measurement Methods ◽  
Data Sets ◽  
Random Effects Model ◽  
Limits Of Agreement ◽  
Continuous Measurements ◽  
Multiple Measurements ◽  
The Mean

Abstract Background To assess the agreement of continuous measurements between a number of observers, Jones et al. introduced limits of agreement with the mean (LOAM) for multiple observers, representing how much an individual observer can deviate from the mean measurement of all observers. Besides the graphical visualisation of LOAM, suggested by Jones et al., it is desirable to supply LOAM with confidence intervals and to extend the method to the case of multiple measurements per observer.Methods We reformulate LOAM under the assumption the measurements follow an additive two-way random effects model. Assuming this model, we provide estimates and confidence intervals for the proposed LOAM. Further, this approach is easily extended to the case of multiple measurements per observer.Results The proposed method is applied on two data sets to illustrate its use. Specifically, we consider agreement between measurements regarding tumour size and aortic diameter. For the latter study, three measurement methods are considered. Conclusions The proposed LOAM and the associated confidence intervals are useful for assessing agreement between continuous measurements.

scholarly journals Integral priors for the one way random effects model

2007 ◽  
Vol 2 (1) ◽  
pp. 59-67 ◽  
Author(s):  
Juan Antonio Cano ◽  
Mathieu Kessler ◽  
Diego Salmerón
Keyword(s):  
Random Effects ◽  
Random Effects Model ◽  
The One
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