### Yale University

Department of Statistics

Seminar

#### Monday, April 22, 1996

Daniel F. Heitjan

Division of Biostatistics

Columbia University School of Public Health

#### Modeling Repeated-Series Longitudinal Data

I will present a model for describing repeated-series longitudinal
data---that is, longitudinal data where each unit may yield
multiple series of the same variable. Such data arise commonly
in ophthalmologic studies, where one obtains measurements on
the same variable for the right and left eyes at each clinic visit.
I model the mean as a linear function of predictors, and assume that
the error term is a sum of a random subject effect and a vector AR(1)
process. I fit the model by maximum likelihood and assess the
adequacy of the error assumptions by an extension of the empirical
semivariogram. I apply the model to data from a clinical trial
comparing two treatments for ocular hypertension and glaucoma,
with intra-ocular pressure as the primary endpoint. Results suggest
that autocorrelation within and between eyes is a significant feature
of the variance model. Standard errors depend critically on the
variance assumption.

#### Seminar to be held in Room 309, LEPH, 60 College Street@ 4:15 pm