ANALYSIS OF LONGITUDINAL DATA WITH UNEQUALLY SPACED OBSERVATIONS AND TIME-DEPENDENT CORRELATED ERRORS

A linear model for repeated measurements is proposed in which the corr elation structure includes a transformation of the time scale. This tr ansformation can produce nonstationary covariance structures within su bjects with stationarity as a special case. Restricted maximum likelih ood methods for parameter estimation are discussed. The method is appl ied to simulated data as well as speech recognition data from the Iowa Cochlear Implant Project, The growth curve for this audiologic perfor mance measure is shown together with estimates of the standard errors of predictions at given months.