Aalen, O.O. 1989. A linear regression model for the analysis of life times. Statistics in Medicine, 8, 907–925. (Cited on p. 189.)
Agresti, A. 1984. Analysis of Ordinal Categorical Data. New York: Wiley. (Cited on p. 131.)
Agresti, A. 1990. Categorical Data Analysis. New York: Wiley. (Cited on p. 131.)
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.)
Anderson, J.A. 1972. Separate sample logistic discrimination. Biometrika, 59, 19–35. (Cited on pp. 30 and 108.)
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.)
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.)
Aranda-Ordaz, F.J. 1983. An extension of the proportional hazards model for grouped data. Biometrics, 39, 109–117. (Cited on p. 188.)
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.)
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.)
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.)
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.)
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.)
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.)
Barlow, W.E. 1994. Robust variance estimation for the case-cohort design. Biometrics, 50, 1064–1072. (Cited on p. 210.)
Barlow, W.E. and Prentice, R.L. 1988. Residuals forrelative riskregression. Biometrika, 75, 65–74. (Cited on p. 210.)
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.)
Barnard, G.A. 1949. Statistical inference (with discussion). Journal of the Royal Statistical Society B, 11, 115–149. (Cited on p. 59.)
Barron, B.A. 1977. The effects of misclassification on the estimation of relative risk. Biometrics, 33, 414–418. (Cited on p. 236.)
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.)
Begg, C.B. and Gray, R. 1984. Calculation of polychotomous logistic regression parameters using individualized regressions. Biometrika, 71, 11–18. (Cited on p. 130.)
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.)
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.)
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.)
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.)
Berkson, J. 1950. Are there two regressions?Journal of the American Statistical Association, 45, 164–180. (Cited on p. 237.)
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.)
Berzuini, C., Dawid, A.P., and Bernardinelli, L. (editors) 2012. Causality. Chichester: Wiley. (Cited on p. 61.)
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.)
Besag, J.E. 1977. Efficiency of pseudo-likelihood estimates for simple Gaussian fields. Biometrika, 64, 616–618. (Cited on p. 261.)
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.)
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.)
Borgan, Ø. and Langholz, B. 1993. Nonparametric estimation of relative mortality from nested case-control studies. Biometrics, 49, 593–602. (Cited on p. 189.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Breslow, N.E. 1981. Odds ratio estimators when the data are sparse. Biometrika, 68, 73–84. (Cited on p. 61.)
Breslow, N.E. 1996. Statistics in epidemiology: the case-control study. Journal of the American Statistical Association, 91, 14–28. (Cited on p. 29.)
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.)
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.)
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.)
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.)
Breslow, N.E. and Liang, K.Y. 1982. The variance of the Mantel-Haenszel estimator. Biometrics, 38, 943–952. (Cited on p. 61.)
Breslow, N.E. and Powers, W. 1978. Are there two logistic regressions for retrospective studies?Biometrics, 34, 100–105. (Cited on p. 108.)
Breslow, N.E. and Zhao, L.P. 1988. Logistic regression for stratified case-control studies. Biometrics, 44, 891–899. (Cited on p. 157.)
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.)
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.)
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.)
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.)
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.)
Buonaccorsi, J.P. 2010. Measurement Error. Models, Methods and Applications. Chapman & Hall/CRC. (Cited on p. 236.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Cochran, W.G. 1954. The combination of estimates from different experiments. Biometrics, 10, 101–129. (Cited on p. 251.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Cosslett, S. 1981. Maximum likelihood estimators for choice-based samples. Econometrica, 49, 1289–1316. (Cited on pp. 108 and 157.)
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.)
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.)
Cox, D.R. 1958b. Two further applications of a model for binary regression. Biometrika, 45, 562–565. (Cited on p. 82.)
Cox, D.R. 1961. Tests of separate families of hypotheses, in Proc. 4th Berkeley Symp., 1, pp. 105–123. (Cited on p. 261.)
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.)
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.)
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.)
Cox, D.R. 1975. Partial likelihood. Biometrika, 62, 269–276. (Cited on p. 186.)
Cox, D.R. 2006. Principles of Statistical Inference. Cambridge: Cambridge University Press. (Cited on p. 261.)
Cox, D.R. and Lewis, P.A.W. 1966. The Statistical Analysis of Series of Events. London: Methuen. (Cited on p. 131.)
Cox, D.R. and Oakes, D. 1984. Analysis of Survival Data. London: Chapman and Hall. (Cited on p. 187.)
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.)
Cox, D.R. and Wermuth, N. 2004. Causality: a statistical view. International Statistical Review, 72, 285–305. (Cited on p. 61.)
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.)
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.)
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.)
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.)
De Stavola, B.L. and Cox, D.R. 2008. On the consequences of overstratification. Biometrika, 95, 992–996. (Cited on p. 109.)
DerSimonian, R. and Laird, N. 1986. Meta-analysis in clinical trials. Controlled Clinical Trials, 7, 177–188. (Cited on p. 251.)
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.)
Doll, R. and Bradford Hill, A. 1950. Smoking and carcinoma of the lung. British Medical Journal, 2, 739–748. (Cited on p. 26.)
Domowitz, I. and Sartain, R.L. 1999. Determinants of the consumer bankruptcy decision. Journal of Finance, 54, 403–420. (Cited on p. 28.)
Drescher, K. and Schill, W. 1991. Attributable risk estimation from case-control data via logistic regression. Biometrics, 47, 1247–1256. (Cited on p. 110.)
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.)
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.)
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.)
Dupont, W.D. 1988. Power calculations for matched case-control studies. Biometrics, 44, 1157–1168. (Cited on p. 82.)
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.)
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.)
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.)
Farrington, C.P. 1995. Relative incidence estimation from case series for vaccine safety evaluation. Biometrics, 51, 228–235. (Cited on p. 131.)
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.)
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.)
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.)
Firth, D. and de Menezes, R.X. 2004. Quasi-variances. Biometrika, 91, 65–80. (Cited on p. 61.)
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.)
Fisher, R.A. 1935. The logic of inductive inference (with discussion). Journal of the Royal Statistical Society, 98, 39–82. (Cited on p. 60.)
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.)
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.)
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.)
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.)
Gail, M.H. 1998. Case-control study, hospital-based, in Encyclopedia of Biostatistics, Volume 1, p. 514. Chichester: Wiley. (Cited on p. 30.)
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.)
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.)
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.)
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.)
Godambe, V.P. 1960. An optimum property of regular maximum likelihood estimation. Annals of Mathematical Statistics, 31, 1208–1212. (Cited on p. 261.)
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.)
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.)
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.)
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.)
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.)
Greenland, S. 1982. The effect of misclassification in matched-pair case-control studies. American Journal of Epidemiology, 116, 402–406. (Cited on p. 237.)
Greenland, S. 1986. Adjustment of risk ratios in case-base studies (hybrid epidemiologic designs). Statistics in Medicine, 5, 579–584. (Cited on p. 209.)
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.)
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.)
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.)
Greenland, S., Pearl, J., and Robins, J.M. 1999. Causal diagrams for epidemiologic research. Epidemiology, 10, 37–48. (Cited on p. 7.)
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.)
Gustafson, P. 2003. Measurement Error and Misclassification in Statistics and Epidemiology. 2nd edn. Chapman & Hall/CRC. (Cited on p. 236.)
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.)
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.)
Hedges, L.V. and Olkin, I. 1985. Statistical Methods for Meta-Analyses. San Diego, Calif.: Academic Press. (Cited on p. 250.)
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.)
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.)
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.)
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.)
Higgins, J.P. and Thompson, S.G. 2002. Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21, 1539–1558. (Cited on p. 251.)
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.)
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.)
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.)
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.)
Hughes, M.D. 1993. Regression dilution in the proportional hazards model. Biometrics, 49, 1056–1066. (Cited on p. 238.)
Hui, S.L. and Walter, S.D. 1980. Estimating the error rates of diagnostic tests. Biometrics, 36, 167–171. (Cited on p. 236.)
Jackson, M. 2009. Disadvantaged through discrimination? The role of employers in social stratification. British Journal of Sociology, 60, 669–692. (Cited on p. 79.)
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.)
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.)
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.)
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.)
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.)
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.)
King, G. and Zeng, L. 2001a. Explaining rare events in international relations. International Organization, 55, 693–715. (Cited on p. 30.)
King, G. and Zeng, L. 2001b. Improving forecasts of state failure. World Politics, 53, 623–658. (Cited on p. 28.)
King, G. and Zeng, L. 2001c. Logistic regression in rare events data. Political Analysis, 9, 137–163. (Cited on p. 30.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Kuritz, S.J. and Landis, J.R. 1988a. Attributable risk estimation from matched case-control data. Biometrics, 44, 355–367. (Cited on p. 110.)
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.)
Langholz, B. 2010. Case-control studies = odds ratios: blame the retrospective model. Epidemiology, 21, 10–12. (Cited on p. 30.)
Langholz, B. and Borgan, Ø. 1995. Counter-matching: a stratified nested case-control sampling method. Biometrika, 82, 69–79. (Cited on p. 187.)
Langholz, B. and Borgan, Ø. 1997. Estimation of absolute risk from nested case-control data. Biometrics, 53, 767–774. (Cited on p. 189.)
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.)
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.)
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.)
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.)
Langholz, B. and Thomas, D.C. 1991. Efficiency of cohort sampling designs: some surprising results. Biometrics, 47, 1563–1571. (Cited on p. 189.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Liu, I.-M. and Agresti, A. 1996. Mantel-Haenszel-type inference for cumulative log odds ratios. Biometrics, 52, 1222–1234. (Cited on p. 131.)
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.)
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.)
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.)
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.)
Manski, C.F. and McFadden, D.L. 1981. Structural Analysis of Discrete Data and Econometric Applications. Cambridge, Mass.: MIT Press. (Cited on p. 30.)
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.)
Mantel, N. 1966. Models for complex contingency tables and polychotomous dosage response curves. Biometrics, 22, 83–95. (Cited on p. 130.)
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.)
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.)
Maraganore, D. 2005. Blood is thicker than water: the strengths of family-based case-control studies. Neurology, 64, 408–409. (Cited on p. 158.)
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.)
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.)
Marti, H. and Chavance, M. 2011. Multiple imputation analysis of case-cohort studies. Statistics in Medicine, 30, 1595–1607. (Cited on p. 211.)
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.)
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.)
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.)
McCullagh, P. 1980. Regression models for ordinal data (with discussion). Journal of the Royal Statistical Society B, 42, 109–142. (Cited on p. 131.)
McNemar, Q. 1947. Note on the sampling error of the differences between correlated proportions or percentages. Psychometrika, 12, 153–157. (Cited on p. 82.)
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.)
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.)
Miettinen, O.S. 1970. Matching and design efficiency in retrospective studies. American Journal of Epidemiology, 91, 111–118. (Cited on p. 82.)
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.)
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.)
Miettinen, O.S. 1985. The ‘case-control’ study: valid selection of subjects. Journal of Chronic Diseases, 38, 543–548. (Cited on p. 30.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Nan, B. 2004. Efficient estimation for case-cohort studies. The Canadian Journal of Statistics, 32, 403–419. (Cited on p. 211.)
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.)
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.)
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.)
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.)
Neyman, J. and Scott, E.L. 1948. Consistent estimates based on partially consistent observations. Econometrica, 16, 1–32. (Cited on p. 82.)
Nurminen, M. 1989. Analysis of epidemiologic case-base studies for binary data. Statistics in Medicine, 8, 1241–1254. (Cited on p. 209.)
Oakes, D. 1981. Survival times: aspects of partial likelihood. International Statistical Review, 49, 235–252. (Cited on p. 187.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Prentice, R.L. 1976. Use of the logistic model in retrospective studies. Biometrics, 32, 599–606. (Cited on p. 108.)
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.)
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.)
Prentice, R.L. 1986b. On the design of synthetic case-control studies. Biometrics, 42, 301–310. (Cited on p. 187.)
Prentice, R.L. and Breslow, N.E. 1978. Retrospective studies and failure time models. Biometrika, 65, 153–158. (Cited on pp. 82 and 187.)
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.)
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.)
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.)
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.)
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.)
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.)
Reid, N. and Crepeau, H. 1985. Influence functions for proportional hazards regression. Biometrika, 72, 1–9. (Cited on p. 210.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Rothman, K.J., Greenland, S., and Lash, T.L. 2008. Modern Epidemiology. 3rd edn. Philadelphia: Lippincott Williams & Wilkins. (Cited on pp. 30 and 209.)
Rubin, D.B. 1987. Multiple Imputation for Nonresponse in Surveys. New York: Wiley. (Cited on p. 189.)
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.)
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.)
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.)
Samuelsen, S.O. 1997. A pseudolikelihood approach to analysis of nested case-control studies. Biometrika, 84, 379–394. (Cited on p. 188.)
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.)
Sato, T. 1992. Maximum likelihood estimation of the risk ratio in case-cohort studies. Biometrics, 48, 1215–1221. (Cited on p. 209.)
Sato, T. 1994. Risk ratio estimation in case-cohort studies. Environmental Health Perspectives, 102 (Suppl. 8), 53–56. (Cited on p. 209.)
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.)
Schaid, D.J. 1999. Case-parents design for gene-environment interaction. Genetic Epidemiology, 16, 261–273. (Cited on p. 158.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Steenland, K. and Deddens, J.A. 1997. Increased precision using countermatching in nested case-control studies. Epidemiology, 8, 238–242. (Cited on p. 187.)
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.)
Stuart, E. 2010. Matching methods for causal inference. Statistical Science, 25, 1–21. (Cited on p. 82.)
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.)
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.)
Sutton, A.J. and Higgins, J.P.T. 2008. Recent developments in meta-analysis. Statistics in Medicine, 27, 625–650. (Cited on p. 251.)
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.)
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.)
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.)
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.)
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.)
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.)
Thompson, S.K. 1992. Sampling. New York: Wiley. (Cited on p. 261.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
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.)
Whittemore, A.S. 1982. Statistical methods for estimating attributable risk from retrospective data. Statistics in Medicine, 1, 229–243. (Cited on p. 110.)
Whittemore, A.S. 1995. Logistic regression of family data from case-control studies. Biometrika, 82, 57–67. (Cited on p. 158.)
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.)
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.)
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.)
Wild, C.J. 1991. Fitting prospective regression models to case-control data. Biometrika, 78, 705–717. (Cited on pp. 131, 157 and 158.)
Willett, W. 1998. Nutritional Epidemiology. 2nd edn. Oxford University Press. (Cited on p. 237.)
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.)
Woolf, B. 1955. On estimating the relationship between blood group and disease. Annals of Human Genetics, 19, 251–253. (Cited on p. 61.)
Wright, S. 1921. Correlation and causation. Journal of Agricultural Research, 20, 162–177. (Cited on p. 7.)
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.)
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.)
Yates, F. and Cochran, W.G. 1938. The analysis of groups of experiments. Journal of Agricultural Science, 28, 556–580. (Cited on p. 250.)
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.)
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.)
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.)
Zhou, H. and Pepe, M.S. 1995. Auxiliary covariate data in failure time regression. Biometrika, 82, 139–149. (Cited on pp. 190 and 211.)
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.)
