Estimation of a Variance Function, with Application to Immunoassay

S ummary The problem of estimating variances by pooling information from a large number of small samples is tackled. Maximum likelihood methods are shown to be inconsistent, but a modified maximum likelihood method is described which gives consistent estimators. A modified likelihood ratio test of fit is also developed, and the application of these results to immunoassay data is described. Comparison with a regression method shows that if the variance function is given by an exponential model, and the observations are in sets of 2, 3 or 4, the modified maximum likelihood method has much greater efficiency.