An application of linear mixed effects model to assess the agreement between two methods with replicated observations.
We study the problem of assessing the agreement between two methods with any number of replicated observations using linear mixed effects (LME) model with Kronecker product covariance structure in a doubly multivariate set-up. This method can also be used in the case of unbalanced designs when number of replications on each patient is unequal, as well as when the number of replications on each patient by respective methods is unequal. The model is implemented using the MIXED procedure of SAS. We demonstrate our proposed method with three real datasets.
Roy
Anuradha
A
Department of Management Science and Statistics, The University of Texas at San Antonio, San Antonio, Texas 78249, USA. Anuradha.Roy@utsa.edu
D000465:Algorithms; D015982:Bias; D001795:Blood Pressure Determination / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D019937:Diagnostic Techniques and Procedures / Q000592:standards* / Q000706:statistics & numerical data*; D006334:Heart Function Tests / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D015233:Models, Statistical; D015588:Observer Variation; D015203:Reproducibility of Results; D012129:Respiratory Function Tests / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data