ROUND ROBIN ANALYSIS OF VARIANCE VIA MAXIMUM LIKELIHOOD
George Y. Wong · ETS Research Report Series · 1981
ABSTRACT We consider a class of linear models called round robin models which deal specifically with data arising in the interaction of a group of individuals in a round robin setting. Such models provide information not only about individual differences but also about the reciprocity behavior of the interaction partners. We provideaconvergent algorithm for computing the maximum likelihood estimates of the variances and covariances associated with these models. Also, we discuss interval estimation of the linear effects, including fixed and random effects. We present a detailed data analysis on a set of speech activity data using these designs.