ON PREDICTION OF FUTURE OBSERVATION IN GROWTH CURVE MODEL

Rao proposed and compared several approaches for predicting future obs ervations in a growth curve model. The assessment of associated predic tion efficiency for different prediction methods were evaluated by Cro ss-Validation Assessment Error (CVAE). He used three data sets, each w ith a limited number of subjects (13-27) and also with a limited numbe r of repeated measurements (4-7) per subject, to illustrate the predic tion methods. In the present paper, we applied four of the prediction methods discussed by Rao, on a data set with a relatively large number of subjects (174) and also with a larger number of measurements (21) per subject, using the polynomial function and log-linear function. We propose to use the restricted cubic spline function as an alternative growth curve model and compare its performance with the polynomial fu nction and log-linear function. It turns out that, at least for larger data sets such as that used in this paper, the prediction methods per form somewhat better when the growth is described by restricted cubic spline function than when the growth is described by polynomial functi on and log-linear function.