title: Regression models for censored serological data.
abstract: The impact was assessed of censored serological measurements on regression equations fitted to data from panels of sera tested by different laboratories, for the purpose of standardizing serosurvey results to common units. Several methods that adjust for censoring were compared, such as deletion, simple substitution, multiple imputation and censored regression. Simulations were generated from different scenarios for varying proportions of data censored. The scenarios were based on serological panel comparisons tested by different national laboratories and assays as part of the European Sero-Epidemiology Network 2 project. The results showed that the simple substitution and deletion methods worked reasonably well for low proportions of data censored (<20 %). However, in general, the censored regression method gave estimates closer to the truth than the other methods examined under different scenarios, such as types of equations used and violation of regression assumptions. Interval-censored regression produced the least biased estimates for assay data resulting from dilution series. Censored regression produced the least biased estimates in comparison with the other methods examined. Moreover, the results suggest using interval-censored regression methods for assay data resulting from dilution series.
authors.affiliation: Department of Mathematics and Statistics, The Open University, Milton Keynes MK7 6AA, UK.|Department of Statistics, Modelling and Economics, Health Protection Agency, 61 Colindale Avenue, London NW9 5EQ, UK.
authors.forename: George
authors.initials: G
authors.lastname: Kafatos
authors.affiliation: Department of Statistics, Modelling and Economics, Health Protection Agency, 61 Colindale Avenue, London NW9 5EQ, UK.
authors.forename: Nick
authors.initials: N
authors.lastname: Andrews
authors.affiliation: Department of Mathematics and Statistics, The Open University, Milton Keynes MK7 6AA, UK.
authors.forename: Kevin J
authors.initials: KJ
authors.lastname: McConway
authors.affiliation: Department of Mathematics and Statistics, The Open University, Milton Keynes MK7 6AA, UK.
authors.forename: Paddy
authors.initials: P
authors.lastname: Farrington
mesh_terms: D015982:Bias; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D005060:Europe; D006801:Humans; D007753:Laboratories / Q000592:standards*; D015233:Models, Statistical; D012044:Regression Analysis; D015203:Reproducibility of Results; D016036:Seroepidemiologic Studies; D012698:Serologic Tests / Q000592:standards / Q000706:statistics & numerical data*; D013223:Statistics as Topic