Abstract
Establishing a causal association between an occupational exposure and the incidence of cancer requires the consideration of many criteria. One of these is whether an association between level of exposure and risk has been demonstrated. For this purpose an association between an ordinal measure of exposure (e.g. three exposure categories) and risk is generally considered sufficient. Once a causal association has been established with reasonable certainty, interest often focusses on a more quantitative relationship between an absolute measure of exposure and risk — for a given quantity of exposure, what is the increase in risk? In particular, estimates of such relationships are required to inform the process of setting standards for “acceptable” limits of exposure. This paper is relevant mainly to these quantitative estimates of exposure-response relationships.
Supported by a grant from the Institut de recherche en santé et sécurité au travail.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Armstrong BG (1985) Measurement error in the generalised linear model. Comm Statist Simul Comp 14: 529–544
Armstrong BG, Oakes D (1982) The effects of approximation in exposure assessments on estimates of exposure response relationships. Scand J Work Environ Health 8 [Suppl 1]: 20–23
Armstrong BG, Tremblay CG, Cyr D, Thériault GP (1986) Estimating the relationship between exposure to tar volatiles and the incidence of bladder cancer in aluminum smelter workers. Scand J Work Environ Health 12: 486–493
Armstrong BG, Whittemore AS, Howe GR (1989) Analysis of case-control data with covariate measurement error: application to diet and colon cancer. Stat Med 8: 1151–1165
Berkson J (1950) Are there two regressions? J Am Stat Assoc 45: 164–180
Carroll RJ, Spiegelman CH, Lan KK, Bailey KT, Abbott RD (1984) On errors-invariables for binary regression models. Biometrika 71: 19–25
Chen TT (1989) Overview of misclassification in epidemiology. Stat Med 8: 1095–1106
Clayton DG (1988) Models for the analysis of cohort and case-control studies with inaccurately measured exposures. In: Dwyer JH, Lippert P, Feinleib M, Hoffmeister H (eds) Statistical models for longitudinal studies of health. Oxford University Press, New York
Cochran WG (1968) Errors of measurement in statistics. Technometrics 10: 637–666
Doll R, Peto R (1978) Cigarette smoking and bronchial carcinoma: dose and time relationships among regular and lifelong nonsmokers. J Epidemiol Community Health 32: 303–313
Fuller WA (1987) Measurement error models. Wiley, New York
Goldberg MS, Siemiatycki J, Gerin M (1986) Inter-rater agreement in assessing occupational exposure in a case-control study. Br J Ind Med 43: 667–676
Greenland S (1980) The effect of misclassification in the presence of covariates. Am J Epidemiol 112: 564–569
Hanley J, Liddell FDK (1985) Fitting relationships between exposure and standardized mortality ratios. J Occup Med 27: 555–560
Kelsey JL, Thompson WD, Evans AS (1986) Methods in observational epidemiology. Oxford University Press, New York, pp 285–308
Kendall M, Stuart A (1979) The advanced theory of statistics vol 2. MacMillan, New York, pp 399–443
Kupper L (-1984) Effects of the use of unreliable surrogate variables on the validity of epidemiological research studies. Am J Epidemiol 120: 643–648
Lagakos S (1987) Effects of mismodelling and mismeasuring explanatory variables on tests of their association with a response variable. Stat Med 7: 257–274
McDonald JC, McDonald AD, Armstrong BG, Sebastien P (1986) Cohort mortality study of vermiculite miners exposed to tremolite. Br J Ind Med 43: 436–444
Pepe M, Self SG, Prentice RL (1989) Further results on covariate measurement errors in cohort studies with time to response data. Stat Med 8: 1167–1178
Prentice RL (1982) Covariate measurement error and parameter estimation in a failure time regression model. Biometrika 69: 331–342
Prentice RL, Farewell VT (1986) Relative risk and odds ratio regression. Annu Rev Public Health 7: 35–58
Schafer DW (1987) Covariate measurement error in generalised linear models. Biometrika 74: 385–391
Schafer DW, Stefanski LA, Tosteson TD (1989) A measurement error model for binary and ordinal regression. Stat Med 8: 1139–1138
Snedecor GW, Cochran WG (1967) Statistical methods. Iowa State University Press, Iowa, pp 164–167
Stefanski LA, Carroll RJ (1985) Covariate measurement error in logistic regression. Ann Stat 13: 1335–1351
Thériault G, Tremblay C, Cordier S, Gingras S (1984) Bladder cancer in the aluminium industry. Lancet is 947–950
Tosteson TD, Tsiatis AA (1988) The asymptotic relative efficiency of score tests in the generalized linear model with surrogate covariates. Biometrika 75: 507–514
Whittemore AS, Grosser S (1986) Regression methods for data with incomplete covariates. In: Moolgavkar SH, Prentice RR (eds) Modern statistical methods in chronic disease epidemiology. Wiley, New York, pp 19–34
Willett W (1989) An epidemiologic perspective on exposure measurement error. Stat Med 8: 1031–1040
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1990 Springer-Verlag Berlin·Heidelberg
About this paper
Cite this paper
Armstrong, B. (1990). Effects of Measurement Errors on Estimates of Exposure-Response Relationships. In: Band, P. (eds) Occupational Cancer Epidemiology. Recent Results in Cancer Research, vol 120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-84068-5_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-84068-5_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-84070-8
Online ISBN: 978-3-642-84068-5
eBook Packages: Springer Book Archive