CALIBRATION WITH RANDOM SLOPES

We consider the following linear calibration problem. Two scalar quant ities X and Y are related by a simple linear regression of Y on X, and at the calibration step repeated measurements on both X and Y are ava ilable for a number of sampling units. At the prediction step a Y meas urement, possibly together with previously obtained Y measurements, is available for a new sampling unit, and we wish to estimate the corres ponding unknown X. Both the intercept and the slope of the regression are allowed to vary between units, resulting in a random regression co efficient model at the calibration step. As a result, at the predictio n step the unknown X affects both the mean and covariance structure of Y. Point and interval estimates for X are obtained and illustrated on a set of biomedical data.