Semiparametric sieve-type generalized least squares inference

This article considers the problem of statistical inference in linear regression models with dependent errors. A sieve-type generalized least squares (GLS) procedure is proposed based on an autoregressive approximation to the generating mechanism of the errors. The asymptotic properties of the sieve-type GLS estimator are established under general conditions, including mixingale-type conditions as well as conditions which allow for long-range dependence in the stochastic regressors and/or the errors. A Monte Carlo study examines the finite-sample properties of the method for testing regression hypotheses

Standardization of measles, mumps and rubella assays to enable comparisons of seroprevalence data across 21 European countries and Australia

The aim of the European Sero-Epidemiology Network is to establish comparability of the serological surveillance of vaccine-preventable diseases in Europe. The designated reference laboratory (RL) for measles, mumps, rubella (MMR) prepared and tested a panel of 151 sera by the reference enzyme immunoassay (rEIA). Laboratories in 21 countries tested the panel for antibodies against MMR using their usual assay (a total of 16 different EIAs) and the results were plotted against the reference results in order to obtain equations for the standardization of national serum surveys. The RL also tested the panel by the plaque neutralization test (PNT). Large differences in qualitative results were found compared to the RL. Well-fitting standardization equations with R20·8 were obtained for almost all laboratories through regression of the quantitative results against those of the RL. When compared to PNT, the rEIA had a sensitivity of 95·3%, 92·8% and 100% and a specificity of 100%, 87·1% and 92·8% for measles, mumps and rubella, respectively. The need for standardization was highlighted by substantial inter-country differences. Standardization was successful and the selected standardization equations allowed the conversion of local serological results into common units and enabled direct comparison of seroprevalence data of the participating countrie