Authors : Neslihan Iyit and Asir Genc
Abstract: In this study, a Random Intercept Model (RIM) as a special case of Linear Mixed Models (LMMs) implying a Compound Symmetry (CS) variance-covariance structure assumption that each pair of repeated measurements has the same correlation, variance and covariance terms is constituted to a repeated measurements data set obtained from a clinical trial. The superiority of Random Intercept Model (RIM) bringing about the advantage of modeling heterogeneity between subjects than General Linear Model (GLM) for repeated measurements data implying a Variance Components (VC) variance-covariance structure assumption that each pair of repeated measurements are uncorrelated and have constant variance is emphasized.
Neslihan Iyit and Asir Genc, 2009. Constitution of Linear Mixed Models (LMMs) in the Analysis of Correlated Data: Random Intercept Model (RIM) for Repeated Measurements Data. Journal of Modern Mathematics and Statistics, 3: 60-68.