Authors: Sami D. Gabbara & Ghadah A. AL-Sakkal
Abstract: In this paper, we develop a general method to analyze several different kinds of certain crossed repeated measures models (CRMM) which represent many situations occurring in repeated measurements on the same experimental units (individuals). Let be the vector of observations of the individuals. It is assumed that the are jointly normally distributed with mean . We want to test hypotheses about . In order to get powerful tests we make the simplifying assumptions that all measurements have the same variance and every pair of measurements that comes from (i) different bulls and different cows (ii) different bulls but with the same cow (iii) the same bull with different cows; have covariance’s respectively. And every pair of measurements that comes from the same bull and the same cow with treatments of (a) different columns and different rows (b) the same column but different rows (c) different columns but the same row have covariance’s and , respectively. The results of this model can be used to analyze certain 4-way balanced mixed and/or random effects models. This procedure is also useful to analyze any of the mentioned 4-way models by adding any number of fixed effects to the model as long as those added effects do not interact with any random effects already in these models.
Keywords: Coordinate-Free, Mixed Models, Random Models, Repeated Measures Models
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