Premium
Dose Response Analysis Using Robust Covariance Estimation
Author(s) -
Sidik Kurex
Publication year - 2001
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/1521-4036(200102)43:1<63::aid-bimj63>3.0.co;2-0
Subject(s) - jackknife resampling , mathematics , monte carlo method , covariance , statistics , robustness (evolution) , delta method , analysis of covariance , statistic , variance (accounting) , nonlinear regression , regression analysis , estimator , biochemistry , chemistry , accounting , business , gene
A dose response analysis is robustified by estimating the asymptotic covariance of the fitted model parameters by the approximate information sandwich (a sandwich statistic) under a heterogeneous variance. The robust method is described by using a nonlinear four‐parameter regression model. The usual, robust, bootstrap, and jackknife estimates of the asymptotic variance are examined for the bioassay data. Under the response of a normal distribution with changing variances over the dose levels, the performance of the usual and robust variances is investigated by Monte Carlo study. It confirms the robustness of the sandwich estimate and shows the non‐accuracy of the usual asymptotic variance estimates of fitted model parameters under the different forms of nonconstant variance structures.