Abstract
We consider the following linear calibration problem. Two scalar quantities 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 available for a number of sampling units. At the prediction step a Y measurement, possibly together with previously obtained Y measurements, is available for a new sampling unit, and we wish to estimate the corresponding unknown X. Both the intercept and the slope of the regression are allowed to vary between units, resulting in a random regression coefficient model at the calibration step. As a result, at the prediction 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 biomédical data. Bootstrap; Population profile model; Random coefficient model; Repeated measures.
Original language | English |
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Pages (from-to) | 439-449 |
Number of pages | 11 |
Journal | Biometrika |
Volume | 85 |
Issue number | 2 |
DOIs | |
State | Published - 1998 |