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 provide a convergent 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. (38pp.)