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References

Published online by Cambridge University Press:  05 April 2014

Ruth H. Keogh  and
D. R. Cox
Ruth H. Keogh
Affiliation:
London School of Hygiene and Tropical Medicine
D. R. Cox
Affiliation:
University of Oxford
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Case-Control Studies , pp. 262 - 280
Publisher: Cambridge University Press
Print publication year: 2014

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References

Aalen, O.O. 1989. A linear regression model for the analysis of life times. Statistics in Medicine, 8, 907–925. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Agresti, A. 1984. Analysis of Ordinal Categorical Data. New York: Wiley. (Cited on p. 131.)Google Scholar
Agresti, A. 1990. Categorical Data Analysis. New York: Wiley. (Cited on p. 131.)Google Scholar
Andersen, P.K., Borgan, Ø., Gill, R., and Keiding, N. 1993. Statistical Models Based on Counting Processes. New York: Springer Verlag. (Cited on p. 187.)CrossRefGoogle Scholar
Anderson, J.A. 1972. Separate sample logistic discrimination. Biometrika, 59, 19–35. (Cited on pp. 30 and 108.)CrossRefGoogle Scholar
Andrieu, N., Goldstein, A.M., Thomas, D.C., and Langholz, B. 2001. Counter-matching in studies of gene-environment interaction: efficiency and feasibility. American Jour;nal of Epidemiology, 153, 265–274. (Cited on p. 188.)Google ScholarPubMed
Anzures-Cabrera, J. and Higgins, J.P. 2010. Graphical displays for univariate meta-analysis: an overview with suggestions for practice. Research Synthesis Methods, 1, 66–80. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Aranda-Ordaz, F.J. 1983. An extension of the proportional hazards model for grouped data. Biometrics, 39, 109–117. (Cited on p. 188.)CrossRefGoogle ScholarPubMed
Armitage, P. 1975. The use of the cross-ratio in aetiological surveys, in Perspectives in Probability and Statistics, pp. 349–355. London: Academic Press. (Cited on p. 109.)Google Scholar
Armstrong, B., Tremblay, C., Baris, D., and Theriault, G. 1994. Lung cancer mortality and polynuclear aromatic hydrocarbons: a case-cohort study of aluminum production workers in Arvida, Quebec, Canada. American Journal of Epidemiology, 139, 250–262. (Cited on p. 194.)CrossRefGoogle ScholarPubMed
Armstrong, B.G., Whittemore, A.S., and Howe, G.R. 1989. Analysis of case-control data with covariate measurement error: application to diet and colon cancer. Statistics in Medicine, 8, 1151–1163. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Austin, H. and Flanders, W.D. 2003. Case-control studies of genotypic relative risks using children of cases as controls. Statistics in Medicine, 22, 129–145. (Cited on p. 158.)CrossRefGoogle ScholarPubMed
Austin, H., Perkins, L.L., and Martin, D.O. 1997. Estimating a relative risk across sparse case-control and follow-up studies: a method for meta-analysis. Statistics in Medicine, 16, 1005–1015. (Cited on p. 251.)3.0.CO;2-N>CrossRefGoogle ScholarPubMed
Barlow, R.E., Bartholomew, D.J., Bremner, J.M., and Brunk, H.D. 1972. Statistical Inference Under Order Restrictions. New York: Wiley. (Cited on p. 131.)Google Scholar
Barlow, W.E. 1994. Robust variance estimation for the case-cohort design. Biometrics, 50, 1064–1072. (Cited on p. 210.)CrossRefGoogle ScholarPubMed
Barlow, W.E. and Prentice, R.L. 1988. Residuals forrelative riskregression. Biometrika, 75, 65–74. (Cited on p. 210.)CrossRefGoogle Scholar
Barlow, W.E., Ichikawa, L., Rosner, D., and Izumi, S. 1999. Analysis of case-cohort designs. Journal of Clinical Epidemiology, 52, 1165–1172. (Cited on p. 210.)CrossRefGoogle ScholarPubMed
Barnard, G.A. 1949. Statistical inference (with discussion). Journal of the Royal Statistical Society B, 11, 115–149. (Cited on p. 59.)Google Scholar
Barron, B.A. 1977. The effects of misclassification on the estimation of relative risk. Biometrics, 33, 414–418. (Cited on p. 236.)CrossRefGoogle ScholarPubMed
Becher, H. 1991. Alternative parametrization of polychotomous models: theory and application to matched case-control studies. Statistics in Medicine, 10, 375–382. (Cited on p. 131.)CrossRefGoogle Scholar
Begg, C.B. and Gray, R. 1984. Calculation of polychotomous logistic regression parameters using individualized regressions. Biometrika, 71, 11–18. (Cited on p. 130.)CrossRefGoogle Scholar
Benichou, J. 1991. Methods of adjustment for estimating the attributable risk in case-control studies: a review. Statistics in Medicine, 10, 1753–1773. (Cited on p. 110.)CrossRefGoogle ScholarPubMed
Benichou, J. and Gail, M.H. 1990. Variance calculations and confidence intervals for estimates of the attributable risk based on logistic models. Biometrics, 46, 991–1003. (Cited on p. 109.)CrossRefGoogle ScholarPubMed
Benichou, J. and Gail, M.H. 1995. Methods of inference for estimates of absolute risk derived from population-based case-control studies. Biometrics, 51, 182–194. (Cited on p. 60.)CrossRefGoogle ScholarPubMed
Benichou, J., Byrne, C., and Gail, M.H. 1997. An approach to estimating exposure-specific rates of breast cancer from a two-stage case-control study within a cohort. Statistics in Medicine, 16, 133–151. (Cited on p. 150.)3.0.CO;2-C>CrossRefGoogle Scholar
Berkson, J. 1950. Are there two regressions?Journal of the American Statistical Association, 45, 164–180. (Cited on p. 237.)CrossRefGoogle Scholar
Bernstein, J.L., Langholz, B., Haile, R.W., Bernstein, L., Thomas, D.C., Stovall, M.et al. 2004. Study design: evaluating gene-environment interacions in the etiology of breast cancer – the WECARE study. Breast Cancer Research, 6, R199–R214. (Cited on p. 173.)CrossRefGoogle Scholar
Berzuini, C., Dawid, A.P., and Bernardinelli, L. (editors) 2012. Causality. Chichester: Wiley. (Cited on p. 61.)CrossRef
Besag, J.E. 1974. Spatial interaction and the statistical analysis of lattice systems (with discussion). Journal of the Royal Statistical Society B, 36, 192–236. (Cited onp. 261.)Google Scholar
Besag, J.E. 1977. Efficiency of pseudo-likelihood estimates for simple Gaussian fields. Biometrika, 64, 616–618. (Cited on p. 261.)CrossRefGoogle Scholar
Bishop, Y.M., Fienberg, S.E., and Holland, P.W. 1975. Discrete Multivariate Analysis: Theory and Practice. Cambridge, Mass.: MIT Press. (Cited on p. 60.)Google Scholar
Borenstein, M., Hedges, L.V., Higgins, J.P.T., and Rothstein, H.R. 2010. A basic introduction to fixed-effect and random-effects models for meta-analysis. Research Synthesis Methods, 1, 97–111. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Borgan, Ø. and Langholz, B. 1993. Nonparametric estimation of relative mortality from nested case-control studies. Biometrics, 49, 593–602. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Borgan, Ø. and Langholz, B. 1997. Estimation of excess risk from case-control data using Aalen's linear regression model. Biometrics, 53, 690–697. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Borgan, Ø. and Olsen, E.F. 1999. The efficiency of simple and counter-matched nested case-control sampling. Scandinavian Journal ofStatistics, 26, 493–509. (Cited on pp. 188 and 189.)Google Scholar
Borgan, Ø., Goldstein, L., and Langholz, B. 1995. Methods for the analysis of sampled cohort data in the Cox proportional hazards model. Annals ofStatistics, 23, 1749–1778. (Cited on pp. 187, 188 and 189.)Google Scholar
Borgan, Ø., Langholz, B., Samuelsen, S.O., Goldstein, L., and Pogoda, J. 2000. Exposure stratified case-cohort designs. Lifetime Data Analysis, 6, 39–58. (Cited on p. 210.)CrossRefGoogle ScholarPubMed
Bowden, J., Tierney, J.F., Simmonds, M., Copas, A.J., and Higgins, J.P. 2011. Individual patient data meta-analysis of time-to-event outcomes: one-stage versus two-stage approaches for estimating the hazard ratio under a random effects model. Research Synthesis Methods, 2, 150–162. (Cited on p. 251.)CrossRefGoogle Scholar
Bradford Hill, A. 1965. The environment and disease: association or causation?Proceedings of the Royal Society of Medicine, 58, 295–300. (Cited on p. 61.)Google Scholar
Breslow, N.E. 1972. Contribution to the discussion of the paper by D.R. Cox. Journal of the Royal Statistical Society B, 34, 216–217. (Cited on p. 189.)Google Scholar
Breslow, N.E. 1981. Odds ratio estimators when the data are sparse. Biometrika, 68, 73–84. (Cited on p. 61.)CrossRefGoogle Scholar
Breslow, N.E. 1996. Statistics in epidemiology: the case-control study. Journal of the American Statistical Association, 91, 14–28. (Cited on p. 29.)CrossRefGoogle ScholarPubMed
Breslow, N.E. and Cain, K.C. 1988. Logistic regression for two-stage case-control data. Biometrika, 75, 11–20. (Cited on pp. 157 and 158.)CrossRefGoogle Scholar
Breslow, N.E. and Chatterjee, N. 1999. Design and analysis of two-phase studies with binary outcome applied to Wilms tumour prognosis. Applied Statistics, 48, 457–468. (Cited on pp. 157 and 158.)Google Scholar
Breslow, N.E. and Day, N.E. 1980. Statistical Methods in Cancer Research: Volume 1 – The Analysis of Case-Control Studies. Lyons: International Agency for Research on Cancer. (Cited on pp. 29 and 61.)Google Scholar
Breslow, N.E. and Holubkov, R. 1997. Maximum likelihood estimation of logistic regression parameters under two-phase, outcome-dependent sampling. Journal of the Royal Statistical Society B, 59, 447–461. (Cited on pp. 157 and 158.)CrossRefGoogle Scholar
Breslow, N.E. and Liang, K.Y. 1982. The variance of the Mantel-Haenszel estimator. Biometrics, 38, 943–952. (Cited on p. 61.)CrossRefGoogle Scholar
Breslow, N.E. and Powers, W. 1978. Are there two logistic regressions for retrospective studies?Biometrics, 34, 100–105. (Cited on p. 108.)CrossRefGoogle ScholarPubMed
Breslow, N.E. and Zhao, L.P. 1988. Logistic regression for stratified case-control studies. Biometrics, 44, 891–899. (Cited on p. 157.)CrossRefGoogle ScholarPubMed
Breslow, N.E., Day, N.E., Halvorsen, K.T., Prentice, R.L., and Sabai, C. 1978. Estimation of multiple relative risk functions in matched case-control studies. American Journal of Epidemiology, 108, 299–307. (Cited on p. 109.)CrossRefGoogle ScholarPubMed
Breslow, N.E., Lumley, T., Ballantyne, C.M., Chambless, L.E., and Kulich, M. 2009a. Improved Horvitz-Thompson estimation of model parameters from two-phase stratified samples: applications in epidemiology. Statistics in Biosciences, 1, 32–49. (Cited on p. 211.)CrossRefGoogle ScholarPubMed
Breslow, N.E., Lumley, T., Ballantyne, C.M., Chambless, L.E., and Kulich, M. 2009b. Using the whole cohort in the analysis of case-cohort data. American Journal of Epidemiology, 169, 1398–1405. (Cited on p. 211.)CrossRefGoogle ScholarPubMed
Bruzzi, P., Green, S.B., Byar, D.P., Brinton, L.A., and Shairer, C. 1985. Estimating the population attributable risk for multiple risk factors using case-control data. American Journal of Epidemiology, 122, 904–914. (Cited on p. 110.)CrossRefGoogle ScholarPubMed
Bull, S.B. and Donner, A. 1993. A characterization of the efficiency of individualized logistic regressions. The Canadian Journal of Statistics, 21, 71–78. (Cited on p. 130.)CrossRefGoogle Scholar
Buonaccorsi, J.P. 2010. Measurement Error. Models, Methods and Applications. Chapman & Hall/CRC. (Cited on p. 236.)CrossRefGoogle Scholar
Cain, K.C. and Breslow, N.E. 1988. Logistic regression analysis and efficient design for two-stage studies. American Journal of Epidemiology, 128, 1198–1206. (Cited on p. 157.)CrossRefGoogle ScholarPubMed
Carroll, R.J., Spiegelman, C., Lan, K.K, Bailey, K.T., and Abbott, R.D. 1984. On errors-in-variables for binary regression models. Biometrika, 71, 19–26. (Cited on p. 238.)CrossRefGoogle Scholar
Carroll, R.J., Gail, M.H., and Lubin, J.H. 1993. Case-control studies with errors in covariates. Journal of the American Statistical Association, 88, 185–199. (Cited on pp. 237 and 239.)Google Scholar
Carroll, R.J., Wang, S., and Wang, C.Y. 1995. Prospective analysis of logistic case-control studies. Journal of the American Statistical Association, 90, 157–169. (Cited on p. 238.)CrossRefGoogle Scholar
Carroll, R.J., Ruppert, D., Stefanski, L.A., and Crainiceanu, C.M. 2006. Measurement Error in Nonlinear Models: A Modern Perspective. 2nd edn. Chapman & Hall/CRC. (Cited on pp. 236, 237 and 238.)CrossRefGoogle Scholar
Chatterjee, N. and Carroll, R.J. 2005. Semiparametric maximum likelihood estimation exploiting gene-environment independence in case-control studies. Biometrika, 92, 399–418. (Cited on pp. 158 and 159.)CrossRefGoogle Scholar
Chen, H.Y. and Little, R.J.A. 1999. Proportional hazards regression with missing co-variates. Journal of the American Statistical Association, 94, 896–908. (Cited on p. 190.)CrossRefGoogle Scholar
Chen, T. 2001. RE: Methods of adjustment for estimating the attributable risk in case-control studies; a review. Statistics in Medicine, 20, 979–982. (Cited on p. 110.)Google Scholar
Chen, Y.-H. 2002. Cox regression in cohort studies with validation sampling. Journal of the Royal Statistical Society B, 64, 51–62. (Cited on p. 211.)CrossRefGoogle Scholar
Chen, Y.T., Dubrow, R., Zheng, T., Barnhill, R.L., Fine, J., and Berwick, M. 1998. Sunlamp use and the risk of cutaneous malignant melanoma: a population-based case-control study in Connecticut, USA. International Journal of Epidemiology, 27, 758–765. (Cited on pp. 27 and 41.)CrossRefGoogle ScholarPubMed
Cheng, C.L. and Schneeweiss, H. 1998. Polynomial regression with errors in the variables. Journal of the Royal Statistical Society B, 60, 189–199. (Cited on p. 238.)CrossRefGoogle Scholar
Chu, R., Gustafson, P., and Le, N. 2010. Bayesian adjustment for exposure misclas-sification in case-control studies. Statistics in Medicine, 29, 994–1003. (Cited on p. 236.)Google ScholarPubMed
Cochran, W.G. 1954. The combination of estimates from different experiments. Biometrics, 10, 101–129. (Cited on p. 251.)CrossRefGoogle Scholar
Cochran, W.G. 1965. The planning of observational studies of human populations (with discussion). Journal of the Royal Statistical Society A, 128, 234–265. (Cited on pp. 61 and 81.)CrossRefGoogle Scholar
Cole, S.R., Chu, H., and Greenland, S. 2006. Multiple-imputation for measurement error correction. International Journal of Epidemiology, 35, 1074–1081. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Cologne, J.B. and Langholz, B. 2003. Selecting controls for assessing interaction in nested case-control studies. Journal of Epidemiology, 13, 193–202. (Cited on p. 188.)CrossRefGoogle ScholarPubMed
Cologne, J.B., Sharp, G.B., Neriishi, K., Verkasalo, P.K., Land, C.E., and Nakachi, K. 2004. Improving the efficiency of nested case-control studies of interaction by selection of controls using counter-matching on exposure. International Journal of Epidemiology, 33, 485–492. (Cited on p. 188.)CrossRefGoogle ScholarPubMed
Cook, J.R. and Stefanski, L.A. 1994. Simulation-extrapolation estimation in parametric measurement error models. Journal of the American Statistical Association, 89, 1314–1328. (Cited on p. 237.)CrossRefGoogle Scholar
Cornfield, J. 1951. A method of estimating comparative rates from clinical data. Applications to cancer of the lung, breast and cervix. Journal of the National Cancer Institute, 11, 1269–1275. (Cited on pp. 29 and 30.)Google ScholarPubMed
Cornfield, J., Haenszel, W., Hammond, E.C., Lilienfeld, A.M., Shimkin, M.B., and Wynder, E.L. 1959. Smoking and lung cancer: recent evidence and a discussion of some questions. Journal of the National Cancer Institute, 22, 173–203. Reprinted in International Journal of Epidemiology 38 (2009), 1175-1191. (Cited on pp. 61 and 251.)Google Scholar
Cosslett, S. 1981. Maximum likelihood estimators for choice-based samples. Econometrica, 49, 1289–1316. (Cited on pp. 108 and 157.)CrossRefGoogle Scholar
Cox, D.R. 1955. Some statistical methods connected with series of events (with discussion). Journal of the Royal Statistical Society B, 17, 129–164. (Cited on p. 60.)Google Scholar
Cox, D.R. 1958a. The regression analysis of binary sequences (with discussion). Journal of the Royal Statistical Society B, 20, 215–242. (Cited on p. 61.)Google Scholar
Cox, D.R. 1958b. Two further applications of a model for binary regression. Biometrika, 45, 562–565. (Cited on p. 82.)CrossRefGoogle Scholar
Cox, D.R. 1961. Tests of separate families of hypotheses, in Proc. 4th Berkeley Symp., 1, pp. 105–123. (Cited on p. 261.)Google Scholar
Cox, D.R. 1962. Further results on tests of separate families of hypotheses. Journal of the Royal Statistical Society B, 24, 406–424. (Cited on p. 261.)Google Scholar
Cox, D.R. 1966. Some procedures connected with the logistic qualitative response curve, in Festschrift for J. Neyman, pp. 55–71. London: Wiley. (Cited on p. 238.)Google Scholar
Cox, D.R. 1972. Regression models and life tables. Journal of the Royal Statistical Society Series B, 34, 187–202. (Cited on pp. 186 and 189.)Google Scholar
Cox, D.R. 1975. Partial likelihood. Biometrika, 62, 269–276. (Cited on p. 186.)CrossRefGoogle Scholar
Cox, D.R. 2006. Principles of Statistical Inference. Cambridge: Cambridge University Press. (Cited on p. 261.)CrossRefGoogle Scholar
Cox, D.R. and Lewis, P.A.W. 1966. The Statistical Analysis of Series of Events. London: Methuen. (Cited on p. 131.)CrossRefGoogle Scholar
Cox, D.R. and Oakes, D. 1984. Analysis of Survival Data. London: Chapman and Hall. (Cited on p. 187.)Google Scholar
Cox, D.R. and Snell, E.J. 1989. Analysis of Binary Data. 2nd edn. London: Chapman and Hall. (Cited on pp. 61, 82 and 109.)Google Scholar
Cox, D.R. and Wermuth, N. 2004. Causality: a statistical view. International Statistical Review, 72, 285–305. (Cited on p. 61.)Google Scholar
Cox, D.R. and Wong, M.Y. 2004. A simple procedure for the selection of significant effects. Journal of the Royal Statistical Society B, 66, 395–400. (Cited on p. 188.)CrossRefGoogle Scholar
Dahm, C.C., Keogh, R.H., Spencer, E.A., Greenwood, D.C., Key, T.J., Fentiman, I.S.et al. 2010. Dietary fiber and colorectal cancer risk: a nested casecontrol study using food diaries. Journal of the National Cancer Institute, 102, 614–626. (Cited on p. 65.)CrossRefGoogle Scholar
Darby, S.C., Ewertz, M., McGale, P., Bennet, A.M., Blom-Goldman, U., Brønnum, D.et al. 2013. Risk of ischaemic heart disease in women after radiotherapy for breast cancer. New England Journal ofMedicine, 368, 987–998. (Cited on p. 177.)Google ScholarPubMed
Day, N.E., Oakes, S., Luben, R., Khaw, K.T., Bingham, S., Welch, A.et al. 1999. EPIC in Norfolk: study design and characteristics of the cohort. British Journal of Cancer, 80 (Suppl. 1), 95–103. (Cited on p. 185.)Google ScholarPubMed
De Stavola, B.L. and Cox, D.R. 2008. On the consequences of overstratification. Biometrika, 95, 992–996. (Cited on p. 109.)CrossRefGoogle Scholar
DerSimonian, R. and Laird, N. 1986. Meta-analysis in clinical trials. Controlled Clinical Trials, 7, 177–188. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Didelez, V., Kreiner, S., and Keiding, N. 2010. On the use of graphical models for inference under outcome-dependent sampling. Statistical Science, 25, 368–387. (Cited on pp. 7, 30 and 61.)CrossRefGoogle Scholar
Doll, R. and Bradford Hill, A. 1950. Smoking and carcinoma of the lung. British Medical Journal, 2, 739–748. (Cited on p. 26.)CrossRefGoogle ScholarPubMed
Domowitz, I. and Sartain, R.L. 1999. Determinants of the consumer bankruptcy decision. Journal of Finance, 54, 403–420. (Cited on p. 28.)CrossRefGoogle Scholar
Drescher, K. and Schill, W. 1991. Attributable risk estimation from case-control data via logistic regression. Biometrics, 47, 1247–1256. (Cited on p. 110.)CrossRefGoogle ScholarPubMed
Dubin, N. and Pasternack, B.S. 1986. Risk assessment for case-control subgroups by polychotomous logistic regression. American Journal of Epidemiology, 123, 1101–1117. (Cited on p. 130.)CrossRefGoogle ScholarPubMed
Duffy, S.W., Rohan, T.E., Kandel, R., Prevost, T.C., Rice, K., and Myles, J.P. 2003. Misclassification in a matched case-control study with variable matching ratio: application to a study of c-erbB-2 overexpression and breast cancer. Statistics in Medicine, 22, 2459–2468. (Cited on p. 237.)CrossRefGoogle Scholar
Duffy, S.W, Warwick, J., Williams, A.R.W., Keshavarz, H., Kaffashian, F., Rohan, T.E.et al. 2004. A simple model for potential use with a misclassified binary outcome in epidemiology. Journal of Epidemiology and Community Health, 58, 712–717. (Cited on p. 236.)CrossRefGoogle ScholarPubMed
Dupont, W.D. 1988. Power calculations for matched case-control studies. Biometrics, 44, 1157–1168. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
Easton, D.J., Peto, J., and Babiker, A.G. 1991. Floating absolute risk: alternative to relative risk in survival and case-control analysis avoiding an arbitrary reference group. Statistics in Medicine, 10, 1025–1035. (Cited on p. 61.)CrossRefGoogle ScholarPubMed
Edwards, A.W.F. 1963. The measure of information in a 2 × 2 table. Journal of the Royal Statistical Society A, 126, 109–114. (Cited on pp. 30 and 59.)CrossRefGoogle Scholar
Farewell, V.T. 1979. Some results on the estimation of logistic models based on retrospective data. Biometrika, 66, 27–32. (Cited on pp. 30 and 108.)CrossRefGoogle Scholar
Farrington, C.P. 1995. Relative incidence estimation from case series for vaccine safety evaluation. Biometrics, 51, 228–235. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Fearn, T., Hill, D.C., and Darby, S.C. 2008. Measurement error in the explanatory variable of a binary regression: regression calibration and integrated conditional likelihood in studies of residential random and lung cancer. Statistics in Medicine, 27, 2159–2176. (Cited on pp. 97 and 239.)CrossRefGoogle Scholar
Fears, T.R. and Brown, C.C. 1986. Logistic regression methods for retrospective case-control studies using complex sampling procedures. Biometrics, 42, 955–960. (Cited on p. 157.)CrossRefGoogle ScholarPubMed
Feinstein, A.R. 1987. Quantitative ambiguities on matched versus unmatched analyses of the 2 × 2 table for a case-control study. International Journal of Epidemiology, 16, 128–134. (Cited on p. 109.)CrossRefGoogle Scholar
Firth, D. and de Menezes, R.X. 2004. Quasi-variances. Biometrika, 91, 65–80. (Cited on p. 61.)CrossRefGoogle Scholar
Fisher, R.A. 1922. On the interpretation of chi square from contingency tables and the calculation of P*. Journal of the Royal Statistical Society, 85, 87–94. (Cited on p. 60.)CrossRefGoogle Scholar
Fisher, R.A. 1935. The logic of inductive inference (with discussion). Journal of the Royal Statistical Society, 98, 39–82. (Cited on p. 60.)CrossRefGoogle Scholar
Flanders, W.D. and Greenland, S. 1991. Analytic methods for two-stage case-control studies and other stratified designs. Statistics in Medicine, 10, 739–747. (Cited on p. 158.)CrossRefGoogle ScholarPubMed
Flanders, W.D., Dersimonian, R., and Rhodes, P. 1990. Estimation of risk ratios in case-base studies with competing risks. Statistics in Medicine, 9, 423–435. (Cited on p. 209.)CrossRefGoogle ScholarPubMed
Freedman, L.S., Fainberg, V., Kipnis, V., Midthune, D., and Carroll, R.J. 2004. A new method for dealing with measurement error in explanatory variables of regression models. Biometrics, 60, 172–181. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Freedman, L.S., Midthune, D., Carroll, R.J., and Kipnis, V. 2008. A comparison of regression calibration, moment reconstruction and imputation for adjusting for covariate measurement error in regression. Statistics in Medicine, 27, 5195–5216. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Gail, M.H. 1998. Case-control study, hospital-based, in Encyclopedia of Biostatistics, Volume 1, p. 514. Chichester: Wiley. (Cited on p. 30.)Google Scholar
Gail, M.H., Wieand, S., and Piantadosi, S. 1984. Biased estimates of treatment effect in randomized experiments with nonlinear regression and omitted covariates. Biometrika, 71, 431–444. (Cited on pp. 52, 61 and 109.)CrossRefGoogle Scholar
Gatto, N.M., Campbell, U.B., Rundle, A.G., and Ahsan, H. 2004. Further development of the case-only design for assessing gene-environment interaction: evaluation of and adjustment for bias. International Journal ofEpidemiology, 33, 1014–1024. (Cited on p. 131.)Google ScholarPubMed
Gauderman, W.J., Witte, J.S., and Thomas, D.C. 1999. Family-based association studies. Journal of the National Cancer Institute Monographs, 26, pp. 31–37. (Cited on p. 158.)Google Scholar
Gebregziabher, M., Guimaraes, P., Cozen, W., and Conti, D.V. 2010. A polytomous conditional likelihood approach for combining matched and unmatched case-control studies. Statistics in Medicine, 29, 1004–1013. (Cited on p. 131.)Google ScholarPubMed
Godambe, V.P. 1960. An optimum property of regular maximum likelihood estimation. Annals of Mathematical Statistics, 31, 1208–1212. (Cited on p. 261.)CrossRefGoogle Scholar
Goldstein, L. and Langholz, B. 1992. Asymptotic theory for nested case-control sampling in the Cox regression model. Annals ofStatistics, 20, 1903–1928. (Cited on p. 187.)Google Scholar
Goodman, L.A. and Kruskal, W.H. 1954. Measures of association for cross-classifications. Journal of the American Statistical Association, 49, 732–764. (Cited on p. 59.)Google Scholar
Goodman, L.A. and Kruskal, W.H. 1959. Measures of association for cross-classifications. II. Further discussion and references. Journal of the American Statistical Association, 54, 123–163. (Cited on p. 59.)CrossRefGoogle Scholar
Goodman, L.A. and Kruskal, W.H. 1963. Measures of association for cross-classifications. III. Approximate sampling theory. Journal of the American Statistical Association, 58, 310–364. (Cited on p. 59.)CrossRefGoogle Scholar
Green, J., Berrington de Gonzalez, A., Sweetland, S., Beral, V., Chilvers, C., Crossley, B.et al. 2003. Risk factors for adenocarcinoma and squamous cell carcinoma of the cervix in women aged 20-44 years: the UK National Case-Control Study of Cervical Cancer. British Journal ofCancer, 89, 2078–2086. (Cited on p. 95.)Google ScholarPubMed
Greenland, S. 1982. The effect of misclassification in matched-pair case-control studies. American Journal of Epidemiology, 116, 402–406. (Cited on p. 237.)CrossRefGoogle ScholarPubMed
Greenland, S. 1986. Adjustment of risk ratios in case-base studies (hybrid epidemiologic designs). Statistics in Medicine, 5, 579–584. (Cited on p. 209.)CrossRefGoogle Scholar
Greenland, S. 1989. On correcting for misclassification in twin studies and other matched-pair studies. Statistics in Medicine, 8, 825–829. (Cited on p. 237.)CrossRefGoogle ScholarPubMed
Greenland, S. and Kleinbaum, D.G. 1983. Correcting for misclassification in two-way tables and matched-pair studies. International Journal of Epidemiology, 12, 93–97. (Cited on pp. 236 and 237.)CrossRefGoogle ScholarPubMed
Greenland, S. and Thomas, D.C. 1982. On the need for the rare disease assumption in case-control studies. American Journal of Epidemiology, 116, 547–553. (Cited on pp. 30 and 61.)CrossRefGoogle ScholarPubMed
Greenland, S., Pearl, J., and Robins, J.M. 1999. Causal diagrams for epidemiologic research. Epidemiology, 10, 37–48. (Cited on p. 7.)CrossRefGoogle ScholarPubMed
Guolo, A. and Brazzale, A.R. 2008. A simulation-based comparison of techniques to correct for measurement error in matched case-control studies. Statistics in Medicine, 27, 3755–3775. (Cited on p. 239.)CrossRefGoogle ScholarPubMed
Gustafson, P. 2003. Measurement Error and Misclassification in Statistics and Epidemiology. 2nd edn. Chapman & Hall/CRC. (Cited on p. 236.)CrossRefGoogle Scholar
Gustafson, P., Le, N.D., and Vallee, M. 2002. A Bayesian approach to case-control studies with errors in covariables. Biostatistics, 3, 229–243. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Hanley, J.A., Csizmadi, I., and Collet, J.-P. 2005. Two-stage case-control studies: precision of parameter estimates and considerations in selecting sample size. American Journal of Epidemiology, 162, 1225–1234. (Cited on pp. 138 and 158.)CrossRefGoogle ScholarPubMed
Hedges, L.V. and Olkin, I. 1985. Statistical Methods for Meta-Analyses. San Diego, Calif.: Academic Press. (Cited on p. 250.)Google Scholar
Heid, I.M., Kuchenhoff, H., Miles, J., Kreienbrock, L., and Wichmann, H.E. 2004. Two dimensions of measurement error: classical and Berkson error in residential radon exposure assessment. Journal of Exposure Analysis and Environmental Epidemiology, 14, 365–377. (Cited on p. 237.)Google ScholarPubMed
Hennessy, S., Bilker, W.B., Berlin, J.A., and Strom, B.L. 1999. Factors influencing the optimal case-to-control ratio in matched case-control studies. American Journal of Epidemiology, 149, 195–197. (Cited on p. 82.)CrossRefGoogle Scholar
Hernan, M.A., Hernandez-Diaz, S., and Robins, J.M. 2004. A structural approach to selection bias. Epidemiology, 15, 615–625. (Cited on pp. 7 and 30.)CrossRefGoogle ScholarPubMed
Higgins, J.P. 2008. Commentary: Heterogeneity in meta-analysis should be expected and appropriately quantified. International Journal of Epidemiology, 37, 1158–1160. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Higgins, J.P. and Thompson, S.G. 2002. Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21, 1539–1558. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Higgins, J.P., Thompson, S.G., and Spiegelhalter, D.J. 2009. A re-evaluation of random-effects meta-analysis. Journal of the Royal Statistical Society A, 172, 137–159. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Hirji, K.F., Mehta, C.R., and Patel, N.R. 1988. Exact inference for matched case-control studies. Biometrics, 44, 803–814. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
Hsieh, D.A., Manski, C.F., and McFadden, D. 1985. Estimation of response probabilities from augmented retrospective observations. Journal of the American Statistical Association, 80, 651–662. (Cited on pp. 109, 110 and 157.)CrossRefGoogle Scholar
Huberman, M. and Langholz, B. 1999. Re: ‘Combined analysis of matched and unmatched case-control studies: comparison of risk estimates from different studies’. American Journal of Epidemiology, 150, 219–220. (Cited on p. 251.)CrossRefGoogle Scholar
Hughes, M.D. 1993. Regression dilution in the proportional hazards model. Biometrics, 49, 1056–1066. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Hui, S.L. and Walter, S.D. 1980. Estimating the error rates of diagnostic tests. Biometrics, 36, 167–171. (Cited on p. 236.)CrossRefGoogle ScholarPubMed
Jackson, M. 2009. Disadvantaged through discrimination? The role of employers in social stratification. British Journal of Sociology, 60, 669–692. (Cited on p. 79.)CrossRefGoogle ScholarPubMed
Johnston, W.T., Vial, F., Gettinby, G., Bourne, F.J., Clifton-Hadley, R.S., Cox, D.R.et al. 2011. Herd-level risk factors of bovine tuberculosis in England and Wales after the 2001 foot-and-mouth disease epidemic. International Journal of Infectious Diseases, 15 (12), e833–e840. (Cited on p. 28.)CrossRefGoogle ScholarPubMed
Kalbfleisch, J.D. and Lawless, J.F. 1988. Likelihood analysis of multi-state models for disease incidence and mortality. Statistics in Medicine, 7, 149–160. (Cited on pp. 188 and 210.)CrossRefGoogle ScholarPubMed
Keogh, R.H. and White, I.R. 2013. Using full cohort data in nested case-control and case-cohort studies by multiple imputation. Statistics in Medicine, 32, 4021–4043. (Cited on pp. 185, 186, 190 and 211.)CrossRefGoogle ScholarPubMed
Keogh, R.H., Strawbridge, A., and White, I.R. 2012a. Effects of exposure measurement error on the shape of exposure-disease associations. Epidemiologic Methods, 1, 13–32. (Cited on p. 238.)CrossRefGoogle Scholar
Keogh, R.H., Park, J.Y., White, I.R., Lenjes, M.A.H., McTaggart, A., Bhaniani, A.et al. 2012b. Estimating the alcohol-breast cancer association: a comparison of diet diaries, FFQs and combined measurements. European Journal of Epidemiology, 27, 547–549. (Cited on p. 243.)CrossRefGoogle ScholarPubMed
Khoury, M.J. and Flanders, W.D. 1996. Nontraditional epidemiologic approaches in the analysis of gene-environment interaction: case-control studies with no controls!American Journal of Epidemiology, 144, 207–213. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
King, G. and Zeng, L. 2001a. Explaining rare events in international relations. International Organization, 55, 693–715. (Cited on p. 30.)CrossRefGoogle Scholar
King, G. and Zeng, L. 2001b. Improving forecasts of state failure. World Politics, 53, 623–658. (Cited on p. 28.)CrossRefGoogle Scholar
King, G. and Zeng, L. 2001c. Logistic regression in rare events data. Political Analysis, 9, 137–163. (Cited on p. 30.)CrossRefGoogle Scholar
King, G. and Zeng, L. 2002. Estimating risk and rate levels, ratios and differences in case-control studies. Statistics in Medicine, 21, 1409–1427. (Cited on pp. 60 and 109.)CrossRefGoogle ScholarPubMed
Kipnis, V., Midthune, D., Freedman, L., Bingham, S., Schatzkin, A., Subar, A.et al. 2001. Empirical evidence of correlated biases in dietary assessment instruments and its implications. American Journal of Epidemiology, 153, 394–403. (Cited on p. 237.)CrossRefGoogle ScholarPubMed
Kosinski, A. and Flanders, W. 1999. Evaluating the exposure and disease relationship with adjustment for different types of exposure misclassification: a regression approach. Statistics in Medicine, 18, 2795–2808. (Cited on p. 236.)3.0.CO;2-S>CrossRefGoogle ScholarPubMed
Kuha, J. 2006. Corrections for exposure measurement error in logistic regresion models with an application to nutritional data. Statistics in Medicine, 13, 1135–1148. (Cited on p. 238.)Google Scholar
Kuha, J. and Skinner, C. 1997. Survey Measurement and Process Quality. New York: Wiley. Chap. Categorical data analysis and misclassification, pp. 633–670. (Cited on p. 236.)Google Scholar
Kuha, J., Skinner, C., and Palmgren, J. 1998. Misclassification error, in Encyclopedia of Biostatistics, pp. 2615–2621. 4th edn. New York: Wiley. (Cited on p. 236.)Google Scholar
Kulich, M. and Lin, D.Y. 2004. Improving the efficiency of relative-risk estimation in case-cohort studies. Journal of the American Statistical Association, 99, 832–844. (Cited on p. 211.)CrossRefGoogle Scholar
Kupper, L.L., McMichael, A.J., and Spirtas, R. 1975. A hybrid epidemiologic study design useful in estimating relative risk. Journal of the American Statistical Association, 70, 524–528. (Cited on p. 209.)Google Scholar
Kupper, L.L., Karon, J.M., Kleinbaum, D.G., Morgenstern, H., and Lewis, D.K. 1981. Matching in epidemiologic studies: validity and efficiency considerations. Biometrics, 149, 271–291. (Cited on p. 82.)Google Scholar
Kuritz, S.J. and Landis, J.R. 1987. Attributable risk ratio estimation from matched-pairs case-control data. American Journal of Epidemiology, 125, 324–328. (Cited on p. 110.)CrossRefGoogle ScholarPubMed
Kuritz, S.J. and Landis, J.R. 1988a. Attributable risk estimation from matched case-control data. Biometrics, 44, 355–367. (Cited on p. 110.)CrossRefGoogle ScholarPubMed
Kuritz, S.J. and Landis, J.R. 1988b. Summary attributable risk estimation from unmatched case-control data. Statistics in Medicine, 7, 507–517. (Cited on p. 109.)CrossRefGoogle ScholarPubMed
Langholz, B. 2010. Case-control studies = odds ratios: blame the retrospective model. Epidemiology, 21, 10–12. (Cited on p. 30.)CrossRefGoogle ScholarPubMed
Langholz, B. and Borgan, Ø. 1995. Counter-matching: a stratified nested case-control sampling method. Biometrika, 82, 69–79. (Cited on p. 187.)CrossRefGoogle Scholar
Langholz, B. and Borgan, Ø. 1997. Estimation of absolute risk from nested case-control data. Biometrics, 53, 767–774. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Langholz, B. and Clayton, D. 1994. Sampling strategies in nested case-control studies. Environmental Health Perspectives, 102 (Suppl. 8), 47–51. (Cited on p. 187.)CrossRefGoogle ScholarPubMed
Langholz, B. and Goldstein, L. 1996. Risk set sampling in epidemiological cohort studies. Statistical Science, 11, 35–53. (Cited on pp. 158, 187 and 188.)Google Scholar
Langholz, B. and Goldstein, L. 2001. Conditional logistic analysis of case-control studies with complex sampling. Biostatistics, 2, 63–84. (Cited on pp. 158 and 188.)CrossRefGoogle ScholarPubMed
Langholz, B. and Thomas, D.C. 1990. Nested case-control and case-cohort methods of sampling from a cohort: a critical comparison. American Journal of Epidemiology, 131, 169–176. (Cited on p. 211.)CrossRefGoogle ScholarPubMed
Langholz, B. and Thomas, D.C. 1991. Efficiency of cohort sampling designs: some surprising results. Biometrics, 47, 1563–1571. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Le Cessie, S., Nagelkerke, N., Rosendaal, F.R., van Stralen, K.J., Pomp, E.R., and van. Houwelingen, H.C. 2008. Combining matched and unmatched control groups in case-control studies. American Journal of Epidemiology, 168, 1204–1210. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Lee, H.J., Scott, A.J., and Wild, C.J. 2010. Efficient estimation in multi-phase case-control studies. Biometrika, 97, 361–374. (Cited on p. 158.)CrossRefGoogle Scholar
Levin, B. 1988. Polychotomous logistic regression methods for matched case-control studies with multiple case or control groups (Letter). American Journal of Epidemiology, 128, 445–446. (Cited on p. 131.)CrossRefGoogle Scholar
Liang, K.Y. and Stewart, W.F. 1987. Polychotomous logistic regression methods for matched case-control studies with multiple case or control groups. American Journal of Epidemiology, 125, 720–730. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Liddell, F.D.K., McDonald, J.C., Thomas, D.C., and Cunliffe, S.V. 1977. Methods of cohort analysis: appraisal by application to asbestos mining. Journal of the Royal Statistical Society A, 140, 469–491. (Cited on pp. 164, 186 and 187.)CrossRefGoogle Scholar
Lilienfeld, A.M. and Lilienfeld, D.E. 1979. A century of case-control studies: progress?Journal of Chronic Diseases, 32, 5–13. (Cited on p. 30.)CrossRefGoogle ScholarPubMed
Lin, D.Y. and Ying, Z. 1993. Cox regression with incomplete covariate measurements. Journal of the American Statistical Association, 88, 1341–1349. (Cited on p. 210.)CrossRefGoogle Scholar
Liu, I.-M. and Agresti, A. 1996. Mantel-Haenszel-type inference for cumulative log odds ratios. Biometrics, 52, 1222–1234. (Cited on p. 131.)CrossRefGoogle Scholar
Liu, M., Lu, W., and Tseng, C.-H. 2010. Cox regression in nested case-control studies with auxiliary covariates. Biometrics, 66, 374–381. (Cited on p. 190.)CrossRefGoogle ScholarPubMed
Lubin, J.H. and Gail, M.H. 1984. Biased selection of controls for case-control analyses of cohort studies. Biometrics, 40, 63–75. (Cited on p. 188.)CrossRefGoogle ScholarPubMed
Lynn, H.S. and McCullogh, C.E. 1992. When does it pay to break the matches for analysis of a matched-pairs design?Biometrics, 48, 397–409. (Cited on pp. 82 and 109.)CrossRefGoogle ScholarPubMed
Maclure, M. 1991. The case-crossover design: a method for studying transient effects on the risk of acute events. American Journal of Epidemiology, 133, 144–153. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Manski, C.F. and McFadden, D.L. 1981. Structural Analysis of Discrete Data and Econometric Applications. Cambridge, Mass.: MIT Press. (Cited on p. 30.)Google Scholar
Mansournia, M.A., Hernan, M.A. and Greenland, S. 2013. Matched designs and causal diagrams. International Journal of Epidemiology, 42, 860–869. (Cited on p. 7.)CrossRefGoogle ScholarPubMed
Mantel, N. 1966. Models for complex contingency tables and polychotomous dosage response curves. Biometrics, 22, 83–95. (Cited on p. 130.)CrossRefGoogle ScholarPubMed
Mantel, N. and Haenszel, W. 1959. Statistical aspects of the analysis of data from retrospective studies of disease. Journal of the National Cancer Institute, 22, 719–748. (Cited on pp. 30 and 61.)Google Scholar
Mantel, N. and Hauck, W.W. 1986. Alternative estimators of the common odds ratio for 2 × 2 tables. Biometrics, 42, 199–202. (Cited on p. 61.)CrossRefGoogle ScholarPubMed
Maraganore, D. 2005. Blood is thicker than water: the strengths of family-based case-control studies. Neurology, 64, 408–409. (Cited on p. 158.)CrossRefGoogle ScholarPubMed
Marsh, J.L., Hutton, J.L., and Binks, K. 2002. Removal of radiation dose-response effects: an example of over-matching. British Medical Journal, 325, 327–330. (Cited on p. 74.)CrossRefGoogle ScholarPubMed
Marshall, R.J. and Chisholm, E.M. 1985. Hypothesis testing in the polychotomous logistic model with an application to detecting gastrointestinal cancer. Statistics in Medicine, 4, 337–344. (Cited on p. 130.)CrossRefGoogle ScholarPubMed
Marti, H. and Chavance, M. 2011. Multiple imputation analysis of case-cohort studies. Statistics in Medicine, 30, 1595–1607. (Cited on p. 211.)CrossRefGoogle ScholarPubMed
Martin, D.O. and Austin, H. 2000. An exact method for meta-analysis of case-control and follow-up studies. Epidemiology, 11, 255–260. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Mathew, T. and Nordstrom, K. 1999. On the equivalence of meta-analysis using literature and using individual patient data. Biometrics, 55, 1221–1223. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Mathew, T. and Nordstrom, K. 2010. Comparison of one-step and two-step meta-analysis models using individual patient data. Biometrical Journal, 52, 271–287. (Cited on p. 251.)Google ScholarPubMed
McCullagh, P. 1980. Regression models for ordinal data (with discussion). Journal of the Royal Statistical Society B, 42, 109–142. (Cited on p. 131.)Google Scholar
McNemar, Q. 1947. Note on the sampling error of the differences between correlated proportions or percentages. Psychometrika, 12, 153–157. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
McShane, L., Midthune, D.N., Dorgan, J.F., Freedman, L.S., and Carroll, R.J. 2001. Co-variate measurement error adjustment for matched case-control studies. Biometrics, 57, 62–73. (Cited on pp. 238 and 239.)CrossRefGoogle Scholar
Miettinen, O.S. 1969. Individual matching with multiple controls in the case of all-or-none responses. Biometrics, 25, 339–355. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
Miettinen, O.S. 1970. Matching and design efficiency in retrospective studies. American Journal of Epidemiology, 91, 111–118. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
Miettinen, O.S. 1976. Estimability and estimation in case-referent studies. American Journal of Epidemiology, 103, 226–235. (Cited on pp. 30, 61 and 209.)CrossRefGoogle ScholarPubMed
Miettinen, O.S. 1982. Design options in epidemiologic research: an update. Scandinavian Journal of Work, Environment and Health, 8 (Suppl. 1), 7–14. (Cited on p. 209.)Google ScholarPubMed
Miettinen, O.S. 1985. The ‘case-control’ study: valid selection of subjects. Journal of Chronic Diseases, 38, 543–548. (Cited on p. 30.)CrossRefGoogle ScholarPubMed
Mittleman, M.A., Maclure, M., and Robins, J.M. 1995. Control sampling strategies for case-crossover studies: an assessment of relative efficiency. American Journal of Epidemiology, 142, 91–98. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Moreno, V., Martin, M.L., Bosch, F.X., de Sanjose, S., Torres, F., and Munoz, N. 1996. Combined analysis of matched and unmatched case-control studies: comparison of risk estimates from different studies. American Journal of Epidemiology, 143, 293–300. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Morrissey, M.J. and Spiegelman, D. 1999. Matrix methods for estimating odds ratios with misclassified exposure data: extensions and comparisons. Biometrics, 55, 338–344. (Cited on p. 236.)CrossRefGoogle ScholarPubMed
Muirhead, C.R. and Darby, S.C. 1987. Modelling the relative and absolute risks of radiation-induced cancers. Journal of the Royal Statistical Society A, 150, 83–118. (Cited on p. 188.)CrossRefGoogle Scholar
Mukherjee, B., Liu, I., and Sinha, S. 2007. Analysis of matched case-control data with multiple ordered disease states: possible choices and comparisons. Statistics in Medicine, 26, 3240–3257. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Mukherjee, B., Ahn, J., Liu, I., Rathouz, P.J., and Sanchez, B.N. 2008. Fitting stratified proportional odds models by amalgamating conditional likelihoods. Statistics in Medicine, 27, 4950–4971. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Müller, P. and Roeder, K. 1997. A Bayesian semiparametric model for case-control studies with errors in variables. Biometrika, 84, 523–537. (Cited on p. 238.)CrossRefGoogle Scholar
Nan, B. 2004. Efficient estimation for case-cohort studies. The Canadian Journal of Statistics, 32, 403–419. (Cited on p. 211.)CrossRefGoogle Scholar
Neuhaus, J.M. and Segal, M.R. 1993. Design effects for binary regression models fitted to dependent data. Statistics in Medicine, 12, 1259–1268. (Cited on p. 109.)CrossRefGoogle ScholarPubMed
Neuhaus, J.M., Scott, A.J., and Wild, C.J. 2002. The analysis of retrospective family studies. Biometrika, 89, 23–37. (Cited on p. 159.)CrossRefGoogle Scholar
Neuhaus, J.M., Scott, A.J., and Wild, C.J. 2006. Family-specific approaches to the analysis of case-control family data. Biometrics, 62, 488–494. (Cited on p. 159.)CrossRefGoogle ScholarPubMed
Neuhauser, M. and Becher, H. 1997. Improved odds ratio estimation by post-hoc stratification of case-control data. Statistics in Medicine, 16, 993–1004. (Cited on p. 109.)3.0.CO;2-2>CrossRefGoogle ScholarPubMed
Neyman, J. and Scott, E.L. 1948. Consistent estimates based on partially consistent observations. Econometrica, 16, 1–32. (Cited on p. 82.)CrossRefGoogle Scholar
Nurminen, M. 1989. Analysis of epidemiologic case-base studies for binary data. Statistics in Medicine, 8, 1241–1254. (Cited on p. 209.)CrossRefGoogle ScholarPubMed
Oakes, D. 1981. Survival times: aspects of partial likelihood. International Statistical Review, 49, 235–252. (Cited on p. 187.)Google Scholar
Olkin, I. and Sampson, A. 1998. Comparison of meta-analysis versus analysis of variance of individual patient data. Biometrics, 54, 317–322. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Onland-Moret, N.C., van der A, D.L., van der Schouw, Y.T., Buschers, W., Elias, S.G., van Gils, C.H.et al. 2007. Analysis of case-cohort data: a comparison of different methods. Journal of Clinical Epidemiology, 60, 350–355. (Cited on p. 210.)CrossRefGoogle ScholarPubMed
Pai, J.K., Pischon, T., Ma, J., Manson, J.E., Hankinson, S.E., Joshipura, K.et al. 2004. Inflammatory markers and the risk of coronary heart disease in men and women. New England Journal of Medicine, 16, 2599–2610. (Cited on p. 170.)Google Scholar
Paneth, N., Susser, E., and Susser, M. 2002a. Origins and early development of the case-control study: part 1, early evolution. Sozial- und Praventivmedizin, 47, 282–288. (Cited on p. 30.)CrossRefGoogle Scholar
Paneth, N., Susser, E., and Susser, M. 2002b. Origins and early development of the case-control study: part 2, the case-control study from Lane-Claypon to 1950. Sozial- und Praventivmedizin, 47, 282–288. (Cited on p. 30.)CrossRefGoogle ScholarPubMed
Pearce, N. 1993. What does the odds ratio estimate in a case-control study?International Journal of Epidemiology, 22, 1189–1192. (Cited on p. 30.)CrossRefGoogle ScholarPubMed
Phillips, A. and Holland, P.W. 1986. Estimators of the variance of the Mantel-Haenszel log-odds-ratio estimate. Biometrics, 43, 425–431. (Cited on p. 61.)Google Scholar
Piegorsch, W.W., Weinberg, C.R., and Taylor, J.A. 1994. Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies. Statistics in Medicine, 13, 153–162. (Cited on p. 131.)CrossRefGoogle ScholarPubMed
Pike, M.C., Hill, A.P., and Smith, P.G. 1980. Bias and efficiency in logistic analyses of stratified case-control studies. International Journal of Epidemiology, 9, 89–95. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
Prentice, R.L. 1976. Use of the logistic model in retrospective studies. Biometrics, 32, 599–606. (Cited on p. 108.)CrossRefGoogle ScholarPubMed
Prentice, R.L. 1982. Covariate measurement errors and parameter estimation in a failure time regression model. Biometrika, 69, 331–342. (Cited on pp. 190, 211 and 238.)CrossRefGoogle Scholar
Prentice, R.L. 1986a. A case-cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika, 73, 1–11. (Cited on pp. 209 and 210.)CrossRefGoogle Scholar
Prentice, R.L. 1986b. On the design of synthetic case-control studies. Biometrics, 42, 301–310. (Cited on p. 187.)CrossRefGoogle ScholarPubMed
Prentice, R.L. and Breslow, N.E. 1978. Retrospective studies and failure time models. Biometrika, 65, 153–158. (Cited on pp. 82 and 187.)CrossRefGoogle Scholar
Prentice, R.L. and Pyke, R. 1979. Logistic disease incidence models and case-control studies. Biometrika, 66, 403–411. (Cited on pp. 30, 108, 109 and 130.)CrossRefGoogle Scholar
Prescott, G.J. and Garthwaite, P.H. 2005. Bayesian analysis of misclassified binary data from a matched case-control study with a validation sub-study. Statistics in Medicine, 24, 379–401. (Cited on p. 236.)CrossRefGoogle ScholarPubMed
Raynor, W.J. and Kupper, L.L. 1981. Category-matching of continuous variables in case-control studies. Biometrics, 37, 811–817. (Cited on p. 82.)CrossRefGoogle Scholar
Recchi, E. 1999. Politics as occupational choice: youth self selection for party careers in Italy. European Sociological Review, 15, 107–124. (Cited on p. 27.)CrossRefGoogle Scholar
Redelmeier, D.A. and Tibshirani, R.J. 1997. Association between cellular-telephone calls and motor vehicle collisions. New England Journal of Medicine, 336, 453–458. (Cited on p. 125.)CrossRefGoogle ScholarPubMed
Reeves, G.K., Cox, D.R., Darby, S.C., and Whitley, E. 1998. Some aspects of measurement error in explanatory variables for continuous and binary regression models. Statistics in Medicine, 17, 2157–2177. (Cited on pp. 224,225, 236,237, 238 and 239.)3.0.CO;2-F>CrossRefGoogle ScholarPubMed
Reid, N. and Crepeau, H. 1985. Influence functions for proportional hazards regression. Biometrika, 72, 1–9. (Cited on p. 210.)CrossRefGoogle Scholar
Reilly, M., Torrang, A., and Klint, A. 2005. Re-use of case-control data for analysis of new outcome variables. Statistics in Medicine, 24, 4009–4019. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Rice, K. 2003. Full-likelihood approaches to misclassification of a binary exposure in matched case-control studies. Statistics in Medicine, 22, 3177–3194. (Cited on p. 237.)CrossRefGoogle ScholarPubMed
Rice, K. and Holmans, P. 2003. Allowing for genotyping error in analysis of unmatched case-control studies. Annals of Human Genetics, 67, 165–174. (Cited on p. 237.)CrossRefGoogle ScholarPubMed
Ridout, M. 1989. Summarizing the results of fitting generalized linear models from designed experiments, in Statistical Modelling: Proceedings of GLIM 89, pp. 262–269. New York: Springer. (Cited on p. 61.)Google Scholar
Risch, H.A. and Tibshirani, R.J. 1988. Re: Polychotomous logistic regression methods for matched case-control studies with multiple case or control groups (Letter). American Journal of Epidemiology, 128, 446–448. (Cited on p. 131.)CrossRefGoogle Scholar
Robins, J.M., Breslow, N., and Greenland, S. 1986. Estimators of the Mantel-Haenszel variance consistent in both sparse data and large-strata limiting models. Biometrics, 42, 311–323. (Cited onp. 61.)CrossRefGoogle ScholarPubMed
Robins, J.M., Gail, M.H. and Lubin, J.H. 1986. More on ‘Biased selection of controls for case-control analyses of cohort studies’. Biometrics, 42, 293–299. (Cited on pp. 187 and 188.)CrossRefGoogle Scholar
Robins, J.M., Prentice, R.L., and Blevins, D. 1989. Designs for synthetic case-control studies in open cohorts. Biometrics, 45, 1103–1116. (Cited on p. 187.)CrossRefGoogle ScholarPubMed
Robins, J.M., Rotnitzky, A., and Zhao, L.P. 1994. Estimation of regression coefficients when some regressors are not always observed. Journal of the American Statistical Association, 89, 846–866. (Cited on p. 190.)CrossRefGoogle Scholar
Robinson, L.D. and Jewell, N.P. 1991. Some surprising results about covariate adjustment in logistic regression models. International Statistical Review, 59, 227–240. (Cited on p. 61.)CrossRefGoogle Scholar
Rodrigues, L. and Kirkwood, B. 1990. Case-control designs in the study of common diseases: updates on the demise of the rare disease assumption and the choice of sampling scheme for controls. International Journal of Epidemiology, 19, 205–213. (Cited on pp. 30 and 61.)CrossRefGoogle Scholar
Roeder, K., Carroll, R.J., and Lindsay, B.G. 1996. A semi-parametric mixture approach to case-control studies with errors in covariables. Journal of the American Statistical Association, 91, 722–732. (Cited on p. 239.)CrossRefGoogle Scholar
Rosner, B., Willett, W.C., and Spiegelman, D. 1989. Correction of logistic regression relative risk estimates and confidence intervals for systematic within-person measurement error. Statistics in Medicine, 8, 1051–1069. (Cited on p. 238.)Google ScholarPubMed
Rosner, B., Spiegelman, D., and Willett, W.C. 1990. Correction of logistic regression relative risk estimates and confidence intervals for measurement error: the case of multiple covariates measured with error. American Journal of Epidemiology, 132, 734–745. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Rosner, B., Willett, W. C., and Spiegelman, D. 1992. Correction of logistic regression relative risk estimates and confidence intervals for random within-person measurement error. American Journal of Epidemiology, 136, 1400–1413. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Rothman, K.J., Greenland, S., and Lash, T.L. 2008. Modern Epidemiology. 3rd edn. Philadelphia: Lippincott Williams & Wilkins. (Cited on pp. 30 and 209.)Google Scholar
Rubin, D.B. 1987. Multiple Imputation for Nonresponse in Surveys. New York: Wiley. (Cited on p. 189.)CrossRefGoogle Scholar
Saarela, O., Kulathinal, S., Arjas, E., and Laara, E. 2008. Nested case-control data utilized for multiple outcomes: a likelihood approach and alternatives. Statistics in Medicine, 27, 5991–6008. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Salim, A., Hultman, C., Sparen, P., and Reilly, M. 2009. Combining data from 2 nested case-control studies of overlapping cohorts to improve efficiency. Biostatistics, 10, 70–79. (Cited on p. 189.)Google ScholarPubMed
Samanic, C.M., De Roos, A.J., Stewart, P.A., Rajaraman, P., Waters, M.A., and In-skip, P.D. 2008. Occupational exposure to pesticides and risk of adult brain tumors. American Journal of Epidemiology, 167, 976–985. (Cited on p. 29.)CrossRefGoogle ScholarPubMed
Samuelsen, S.O. 1997. A pseudolikelihood approach to analysis of nested case-control studies. Biometrika, 84, 379–394. (Cited on p. 188.)CrossRefGoogle Scholar
Samuelsen, S.O., Anestad, H., and Skrondal, A. 2007. Stratified case-cohort analysis of general cohort sampling designs. Scandinavian Journal of Statistics, 34 (1), 103–119, 64-81. (Cited on p. 210.)CrossRefGoogle Scholar
Sato, T. 1992. Maximum likelihood estimation of the risk ratio in case-cohort studies. Biometrics, 48, 1215–1221. (Cited on p. 209.)CrossRefGoogle Scholar
Sato, T. 1994. Risk ratio estimation in case-cohort studies. Environmental Health Perspectives, 102 (Suppl. 8), 53–56. (Cited on p. 209.)CrossRefGoogle ScholarPubMed
Saunders, C.L. and Barrett, J.H. 2004. Flexible matching in case-control studies of gene-environment interactions. American Journal of Epidemiology. (Cited on p. 158.)CrossRefGoogle ScholarPubMed
Schaid, D.J. 1999. Case-parents design for gene-environment interaction. Genetic Epidemiology, 16, 261–273. (Cited on p. 158.)3.0.CO;2-M>CrossRefGoogle ScholarPubMed
Scheike, T.H. and Juul, A. 2004. Maximum likelihood estimation for Cox's regression model under nested case-control sampling. Biostatistics, 5, 193–206. (Cited on p. 190.)CrossRefGoogle ScholarPubMed
Schill, W. and Drescher, K. 1997. Logistic analysis of studies with two-stage sampling: a comparison of four approaches. Statistics in Medicine, 16, 117–132. (Cited on pp. 157 and 158.)3.0.CO;2-5>CrossRefGoogle ScholarPubMed
Schill, W., Jockel, K.H., Drescher, K., and Timm, J. 1993. Logistic analysis in case-control studies under validation sampling. Biometrika, 80, 339–352. (Cited on p. 239.)CrossRefGoogle Scholar
Scott, A.J. and Wild, C.J. 1986. Fitting logistic models under case-control or choice-based sampling. Journal of the Royal Statistical Society B, 48, 170–182. (Cited on pp. 109, 157 and 158.)Google Scholar
Scott, A.J. and Wild, C.J. 1991. Logistic regression models in stratified case-control studies. Biometrics, 47, 497–510. (Cited on pp. 131 and 157.)CrossRefGoogle Scholar
Scott, A.J. and Wild, C.J. 1997. Fitting regression models to case-control data by maximum likelihood. Biometrika, 84, 57–71. (Cited on pp. 131 and 157.)CrossRefGoogle Scholar
Scott, A.J. and Wild, C.J. 2001. Case-control studies with complex sampling. Journal of the Royal Statistical Society C, 50, 389–401. (Cited on p. 157.)CrossRefGoogle Scholar
Scott, A.J. and Wild, C.J. 2002. On the robustness of weighted methods for fitting models to case-control data. Journal of the Royal Statistical Society B, 64, 207–219. (Cited on p. 158.)CrossRefGoogle Scholar
Seaman, S.R. and Richardson, S. 2004. Equivalence of prospective and retrospective models in the Bayesian analysis of case-control studies. Biometrika, 91, 15–25. (Cited on p. 109.)CrossRefGoogle Scholar
Self, S.G. and Prentice, R.L. 1988. Asymptotic distribution theory and efficiency results for case-cohort studies. Annals ofStatistics, 16, 64–81. (Cited on p. 210.)Google Scholar
Siegel, D.G. and Greenhouse, S.W. 1973. Validity in estimating relative risk in case-control studies. Journal of Chronic Diseases, 26, 210–225. (Cited on p. 109.)Google Scholar
Siegmund, K.D. and Langholz, B. 2001. Stratified case sampling and the use of family controls. Genetic Epidemiology, 20, 316–327. (Cited on p. 159.)CrossRefGoogle ScholarPubMed
Smith-Warner, S.A., Spiegelman, D., Ritz, J., Albanes, D., Beeson, W.L., Bernstein, L.et al. 2006. Methods for pooling results of epidemiologic studies: the pooling project of prospective studies of diet and cancer. American Journal of Epidemiology, 163, 1053–1064. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Solomon, P.J. 1984. Effect of misspecification of regression models in the analysis of survival data. (Amendment 73 (1986), 245). Biometrika, 71, 291–298. (Cited on p. 189.)CrossRefGoogle Scholar
Spiegelman, D., McDermott, A., and Rosner, B. 1997. Regression calibration method for correcting measurement-error bias in nutritional epidemiology. American Journal of Clinical Nutrition, 65, 1179S–1186S. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Steenland, K. and Deddens, J.A. 1997. Increased precision using countermatching in nested case-control studies. Epidemiology, 8, 238–242. (Cited on p. 187.)CrossRefGoogle ScholarPubMed
Støer, N. and Samuelsen, S. 2012. Comparison of estimators in nested case-control studies with multiple outcomes. Lifetime Data Analysis, 18, 261. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Stuart, E. 2010. Matching methods for causal inference. Statistical Science, 25, 1–21. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
Stukel, T.A., Demidenko, E., Dykes, J., and Karagas, M.R. 2001. Two-stage methods for the analysis of pooled data. Statistics in Medicine, 20, 2115–2130. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Sturmer, T. and Brenner, H. 2002. Flexible matching strategies to increase power and efficiency to detect and estimate gene-environment interactions in case-control studies. American Journal of Epidemiology. (Cited on p. 158.)CrossRefGoogle ScholarPubMed
Sutton, A.J. and Higgins, J.P.T. 2008. Recent developments in meta-analysis. Statistics in Medicine, 27, 625–650. (Cited on p. 251.)CrossRefGoogle ScholarPubMed
Therneau, T.M. and Li, H. 1998. Technical Report Series No. 62, Computing the Cox model for case-cohort designs. Section of Biostatistics, Mayo Clinic, Rochester, Minnesota. (Cited on p. 210.)Google Scholar
Thomas, D.C. 1977. Addendum to: Methods of cohort analysis: appraisal by application to asbestos mining. Journal of the Royal Statistical Society A, 140, 469–491. (Cited on p. 187.)Google Scholar
Thomas, D.C and Greenland, S. 1983. The relative efficiencies of matched and independent sample designs for case-control studies. Journal of Chronic Diseases, 10, 685–697. (Cited on p. 82.)Google Scholar
Thomas, D.C., Goldberg, M., Dewar, R., et al. 1986. Statistical methods for relating several exposure factors to several diseases in case-heterogeneity studies. Statistics in Medicine, 5, 49–60. (Cited on p. 130.)CrossRefGoogle ScholarPubMed
Thomas, L., Stefanski, L., and Davidian, M. 2011. A moment-adjusted imputation method for measurement error models. Biometrics, 67, 1461–1470. (Cited on p. 238.)CrossRefGoogle ScholarPubMed
Thompson, S.G. and Sharp, S.J. 1999. Explaining heterogeneity in meta-analysis: a comparison of methods. Statistics in Medicine, 18, 2693–2708. (Cited on p. 251.)3.0.CO;2-V>CrossRefGoogle ScholarPubMed
Thompson, S.K. 1992. Sampling. New York: Wiley. (Cited on p. 261.)Google ScholarPubMed
Thompson, W.D., Kelsey, J.L., and Walter, S.D. 1982. Cost and efficiency in the choice of matched and unmatched case-control designs. American Journal of Epidemiology, 116, 840–851. (Cited on p. 82.)CrossRefGoogle Scholar
Thürigen, D., Spiegelman, D., Blettner, M., Heuer, C., and Brenner, H. 2000. Measurement error correction using validation data: a review of methods and their applicability in case-control studies. Statistical Methods in Medical Research, 9, 447–474. (Cited on p. 237.)CrossRefGoogle ScholarPubMed
Ury, H.K. 1975. Efficiency of case-control studies with multiple controls per case: continuous or dichotomous data. Biometrics, 31, 643–649. (Cited on p. 82.)CrossRefGoogle ScholarPubMed
VanderWeele, T.J., Hernandez-Diaz, S., and Hernán, M.A. 2010. Case-only geneenvironment interaction studies: when does association imply mechanistic interaction?Genetic Epidemiology, 34, 327–334. (Cited on p. 131.)CrossRefGoogle Scholar
Wacholder, S. and Hartge, P. 1998. Case-control study, in Encyclopedia of Biostatistics, Volume 1, pp. 503–514. Chichester: Wiley. (Cited on pp. 29 and 30.)Google Scholar
Wacholder, S., Gail, M.H., Pee, D., and Brookmeyer, R. 1989. Alternative variance and efficiency calculations for the case-cohort design. Biometrika, 76, 117–123. (Cited on p. 210.)CrossRefGoogle Scholar
Wacholder, S., McLaughlin, J.K., Silverman, D.T., and Mandel, J.S. 1992a. Selection of controls in case-control studies I. Principles. American Journal of Epidemiology, 135, 1019–1028. (Cited on p. 30.)Google ScholarPubMed
Wacholder, S., McLaughlin, J.K., Silverman, D.T., and Mandel, J.S. 1992b. Selection of controls in case-control studies, III. Design options. American Journal of Epidemiology, 135, 1042–1051. (Cited on p. 82.)Google ScholarPubMed
Wang, M. and Hanfelt, J.J. 2009. A robust method for finely stratified familial studies with proband-based sampling. Biostatistics, 10, 364–373. (Cited on p. 159.)CrossRefGoogle ScholarPubMed
Weinberg, C.R. and Sandler, D.P. 1991. Randomized recruitment in case-control studies. American Journal of Epidemiology, 134, 421–432. (Cited on p. 108.)CrossRefGoogle ScholarPubMed
Weinberg, C.R. and Umbach, D.M. 2000. Choosing a retrospective design to assess joint genetic and environmental contributions to risk. American Journal of Epidemiology, 152, 197–203. (Cited on p. 158.)CrossRefGoogle ScholarPubMed
Weinberg, C.R. and Wacholder, S. 1993. Prospective analysis of case-control data under general multiplicative intercept risk models. Biometrika, 80, 461–465. (Cited on p. 109.)Google Scholar
Whitaker, H.J., Farrington, C.P., Spiessens, B. and Musonda, P. 2006. Tutorial in bio-statistics: the self-controlled case series method. Statistics in Medicine, 25, 1768–1797. (Cited on p. 131.)CrossRefGoogle Scholar
Whitaker, H.J., Hocine, M.N., and Farrington, C.P. 2009. The methodology of self-controlled case series studies. Statistical Methods in Medical Research, 18, 7–26. (Cited on pp. 128 and 131.)CrossRefGoogle ScholarPubMed
White, I.R. and Royston, P. 2009. Imputing missing covariate values for the Cox model. Statistics in Medicine, 28, 1982–1998. (Cited on p. 190.)CrossRefGoogle ScholarPubMed
White, I.R., Royston, P., and Wood, A.M. 2011. Multiple imputation using chained equations: issues and guidance for practice. Statistics in Medicine, 30, 377–399. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
White, J.E. 1982. A two stage design for the study of the relationship between a rare exposure and a rare disease. American Journal of Epidemiology, 115, 119–128. (Cited on p. 157.)CrossRefGoogle Scholar
Whittemore, A.S. 1982. Statistical methods for estimating attributable risk from retrospective data. Statistics in Medicine, 1, 229–243. (Cited on p. 110.)CrossRefGoogle ScholarPubMed
Whittemore, A.S. 1995. Logistic regression of family data from case-control studies. Biometrika, 82, 57–67. (Cited on p. 158.)CrossRefGoogle Scholar
Whittemore, A.S. and Halpern, J. 1989. Testing odds-ratio equality for several diseases. Statistics in Medicine, 76, 795–798. (Cited on pp. 130 and 131.)Google Scholar
Whittemore, A.S. and Halpern, J. 1997. Multi-stage sampling in genetic epidemiology. Statistics in Medicine, 16, 153–167. (Cited on pp. 156 and 158.)3.0.CO;2-7>CrossRefGoogle ScholarPubMed
Whittemore, A.S. and Halpern, J. 2003. Logistic regression of family data from retrospective study designs. Genetic Epidemiology, 25, 177–189. (Cited on pp. 158 and 159.)CrossRefGoogle ScholarPubMed
Wild, C.J. 1991. Fitting prospective regression models to case-control data. Biometrika, 78, 705–717. (Cited on pp. 131, 157 and 158.)CrossRefGoogle Scholar
Willett, W. 1998. Nutritional Epidemiology. 2nd edn. Oxford University Press. (Cited on p. 237.)CrossRefGoogle Scholar
Witte, J.S., Gauderman, W.J., and Thomas, D.C. 1999. Asymptotic bias and efficiency in case-control studies of candidate genes and gene-environment interactions: basic family designs. American Journal of Epidemiology, 149, 694–705. (Cited on p. 158.)CrossRefGoogle ScholarPubMed
Woolf, B. 1955. On estimating the relationship between blood group and disease. Annals of Human Genetics, 19, 251–253. (Cited on p. 61.)CrossRefGoogle Scholar
Wright, S. 1921. Correlation and causation. Journal of Agricultural Research, 20, 162–177. (Cited on p. 7.)Google Scholar
Xie, Y. and Manski, C.F. 1989. The logit model and response-based samples. Sociological Methods and Research, 17, 283–302. (Cited on p. 30.)CrossRefGoogle Scholar
Yaghjyan, L., Colditz, G.A., Collins, L.C., Schnitt, S.J., Rosner, B., Vachon, C.et al. 2011. Mammographic breast density and subsequent risk of breast cancer in post-menopausal women according to tumor characteristics. Journal of the National Cancer Institute, 103, 1179–1189. (Cited on p. 112.)CrossRefGoogle Scholar
Yates, F. and Cochran, W.G. 1938. The analysis of groups of experiments. Journal of Agricultural Science, 28, 556–580. (Cited on p. 250.)Google Scholar
Zhang, J. and Borgan, Ø. 1999. Aalen's linear model for sampled risk set data: a large sample study. Lifetime Data Analysis, 5, 351–369. (Cited on p. 189.)CrossRefGoogle ScholarPubMed
Zhang, L., Mukherjee, B., Ghosh, M., Gruber, S., and Moreno, V. 2008. Accounting for error due to misclassification of exposures in case-control studies of geneenvironment interaction. Statistics in Medicine, 27, 2756–2783. (Cited on p. 237.)CrossRefGoogle Scholar
Zhao, L.P., Hsu, L., Holte, S., Chen, Y., Quiaoit, F., and Prentice, R.L. 1998. Combined association and aggregation analysis of data from case-control family studies. Biometrika, 85, 299–315. (Cited on p. 159.)CrossRefGoogle Scholar
Zhou, H. and Pepe, M.S. 1995. Auxiliary covariate data in failure time regression. Biometrika, 82, 139–149. (Cited on pp. 190 and 211.)CrossRefGoogle Scholar
Zota, A.R., Aschengrau, A., Rudel, R.A., and Brody, J.G. 2010. Self-reported chemicals exposure, beliefs about disease causation, and risk of breast cancer in the Cape Cod Breast Cancer and Environment Study: a case-control study. Environmental Health, 9, doi:10.1186/1476-069X-9-40. (Cited on p. 213.)CrossRefGoogle ScholarPubMed

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  • References
  • Ruth H. Keogh, London School of Hygiene and Tropical Medicine, D. R. Cox, University of Oxford
  • Book: Case-Control Studies
  • Online publication: 05 April 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139094757.015
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  • References
  • Ruth H. Keogh, London School of Hygiene and Tropical Medicine, D. R. Cox, University of Oxford
  • Book: Case-Control Studies
  • Online publication: 05 April 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139094757.015
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  • References
  • Ruth H. Keogh, London School of Hygiene and Tropical Medicine, D. R. Cox, University of Oxford
  • Book: Case-Control Studies
  • Online publication: 05 April 2014
  • Chapter DOI: https://doi.org/10.1017/CBO9781139094757.015
Available formats
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