and Qiu, P. (2006). Chapman & Hall, London, 1995.Carroll R.J., Spiegelmann C., Lan K.K., Bailey K.T., and Abbott R.D. statistically independent of the true variable) versus Berkson-type error (i.e. The participants were interviewed with regard to their long-time residential, smoking, and occupational history.
Mathematical Reviews (MathSciNet): MR2101455Wang, L. (2004). Nonparametric methods for solving the Berkson errors-in-variables problem. Error of the Berkson type is involved, when a group's average is assigned to each individual suiting the group's characteristics. We find that the replicate measurements provide further evidence of the multiplicativity by graphically viewing the mean versus single measurements (Figures 3 and 4).Top of pageConclusionsWe conclude that, generally in epidemiology,
and Keles, S. (2004). and Rao, R. The full error is represented in the continuum of a two-dimensional space (compare with Zeger et al., 2000). Mathematical Reviews (MathSciNet): MR2000257 Digital Object Identifier: doi:10.1111/1468-0262.00459Pope, C.
The classical error can induce severe bias on the risk estimate; multiplicative classical error can even distort the dose-response curve. Berkson error may predominate over classical error in cases where exposure data are highly aggregated. Mathematical Reviews (MathSciNet): MR2031013 Digital Object Identifier: doi:10.1111/j.1468-0262.2004.00477.xSchennach, S. P.
For a classical error of 100%, all the observed exposure variance would be due to error, the true exposure variance would be zero, which is the reason for the classical error M., Dominici, F., Curriero, F. However, the smaller number of measurements can clearly be viewed, and a glance at the unit of the axes labelling, 1000Bq/m3 instead of 1Bq/m3 in Figure 3, shows that the radon GSF-report S-626, Neuherberg,, 1989.Kreienbrock L., Kreuzer M., Gerken M., Dingerkus G., Wellmann J., Keller G., and Wichmann H.E.
However, from the biological point of view, several stages of the disease-causing process are distinguished and the term "exposure" is one of the three terms employed (Armstrong, 1990): (1) the concentration, S. (2000). Soc. Generated Tue, 01 Nov 2016 10:26:30 GMT by s_wx1194 (squid/3.5.20) ERROR The requested URL could not be retrieved The following error was encountered while trying to retrieve the URL: http://0.0.0.8/ Connection
Health Phys 2000: 78(3): 268-278.|Article|Gunby J.A., Darby S.C., Miles J.C.H., Green B.M.R., and Cox D.R. navigate to this website Carroll, R. Classical Error Top of pageAbstractMeasurement error in exposure assessment is unavoidable. Berkson Bias Econom.
The curves are drawn based on the expected exposure given the observed exposure and given a certain error model (following the reasoning of the regression calibration method). Residential radon and risk of lung cancer in Eastern Germany. Measurement Error in Nonlinear Models. The value of 0.1 obtained in a controlled exercise with a limit number of measurements can thus be viewed as a minimum error size for the epidemiological studies, where over 10,000 Google Scholar
Mathematical Reviews (MathSciNet): MR2374986 Digital Object Identifier: doi:10.1111/j.0012-9682.2008.00823.xHuwang, L. L. (1991). Stat. Thyroid cancer following scalp irradiation: a reanalysis accounting for uncertainty in dosimetry.
Models for retrospective quantification of indoor radon exposure in case-control studies. Stat Med 1989: 8: 1139-1147.Wichmann H.E., Gerken M., Wellmann J., Kreuzer M., Kreienbrock L., Keller G., Wölke G., and Heinrich J. Am J Epidemiol 2001: 153(1): 42-52.|Article|PubMed|ISI|ChemPort|Kreienbrock L., Poffijn A., Tirmarche M., Feider M., Kies A., and Darby S.C.
et al. (2000). Accept and close | More info. Genet. We found that "external residential radon exposure" as lung cancer predictor involves almost no Berkson error component, whereas the predictor "lung dose" introduces a Berkson error.
NLM NIH DHHS USA.gov National Center for Biotechnology Information, U.S. Econom. The system returned: (22) Invalid argument The remote host or network may be down. Radiat Prot Dosim 1992: 45(Suppl 1/4): 651-656.Reeves G.K., Cox D.R., Darby S.C., and Whitley E.
These internal data allow the estimation of the between-measurement-variability, given that the differences between rooms can be controlled for. B Stat. ISBN1-4200-1013-1. statistically independent from the observed variable) and between additive versus multiplicative structure.
pp.26–32. For example, a multiplicative classical error with SD (on the log-scale) of 0.48, as estimated for the English radon study (Darby et al., 1998), explains about 20% of the observed radon