Skip to main content Accessibility help
×
  • Cited by 44
Publisher:
Cambridge University Press
Online publication date:
April 2014
Print publication year:
2014
Online ISBN:
9781139094757

Book description

The case-control approach is a powerful method for investigating factors that may explain a particular event. It is extensively used in epidemiology to study disease incidence, one of the best-known examples being Bradford Hill and Doll's investigation of the possible connection between cigarette smoking and lung cancer. More recently, case-control studies have been increasingly used in other fields, including sociology and econometrics. With a particular focus on statistical analysis, this book is ideal for applied and theoretical statisticians wanting an up-to-date introduction to the field. It covers the fundamentals of case-control study design and analysis as well as more recent developments, including two-stage studies, case-only studies and methods for case-control sampling in time. The latter have important applications in large prospective cohorts which require case-control sampling designs to make efficient use of resources. More theoretical background is provided in an appendix for those new to the field.

Reviews

'This book will rapidly become the bible for researchers using case control studies. It covers essentially all aspects of such designs and their application.'

David J. Hand - Imperial College London

Refine List

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
×

Contents

References
Aalen, O.O. 1989. A linear regression model for the analysis of life times. Statistics in Medicine, 8 CrossRef | Google Scholar | PubMed, 907–925. (Cited on p. 189.)
Agresti, A. 1984. Analysis of Ordinal Categorical Data. New York Google Scholar: Wiley. (Cited on p. 131.)
Agresti, A. 1990. Categorical Data Analysis. New York Google Scholar: Wiley. (Cited on p. 131.)
Andersen, P.K., Borgan, Ø., Gill, R., and Keiding, N. 1993. Statistical Models Based on Counting Processes. New York CrossRef | Google Scholar: Springer Verlag. (Cited on p. 187.)
Anderson, J.A. 1972. Separate sample logistic discrimination. Biometrika, 59 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 66–80. (Cited on p. 251.)
Aranda-Ordaz, F.J. 1983. An extension of the proportional hazards model for grouped data. Biometrics, 39 CrossRef | Google Scholar | PubMed, 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 Google Scholar: 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar: Wiley. (Cited on p. 131.)
Barlow, W.E. 1994. Robust variance estimation for the case-cohort design. Biometrics, 50 CrossRef | Google Scholar | PubMed, 1064–1072. (Cited on p. 210.)
Barlow, W.E. and Prentice, R.L. 1988. Residuals forrelative riskregression. Biometrika, 75 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 1165–1172. (Cited on p. 210.)
Barnard, G.A. 1949. Statistical inference (with discussion). Journal of the Royal Statistical Society B, 11 Google Scholar, 115–149. (Cited on p. 59.)
Barron, B.A. 1977. The effects of misclassification on the estimation of relative risk. Biometrics, 33 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 375–382. (Cited on p. 131.)
Begg, C.B. and Gray, R. 1984. Calculation of polychotomous logistic regression parameters using individualized regressions. Biometrika, 71 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 133–151. (Cited on p. 150.)
Berkson, J. 1950. Are there two regressions?Journal of the American Statistical Association, 45 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, R199–R214. (Cited on p. 173.)
Berzuini, C., Dawid, A.P., and Bernardinelli, L. (editors) 2012. Causality. Chichester CrossRef | Google Scholar: 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 Google Scholar, 192–236. (Cited onp. 261.)
Besag, J.E. 1977. Efficiency of pseudo-likelihood estimates for simple Gaussian fields. Biometrika, 64 CrossRef | Google Scholar, 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. Google Scholar: 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 CrossRef | Google Scholar | PubMed, 97–111. (Cited on p. 251.)
Borgan, Ø. and Langholz, B. 1993. Nonparametric estimation of relative mortality from nested case-control studies. Biometrics, 49 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 Google Scholar, 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 Google Scholar, 216–217. (Cited on p. 189.)
Breslow, N.E. 1981. Odds ratio estimators when the data are sparse. Biometrika, 68 CrossRef | Google Scholar, 73–84. (Cited on p. 61.)
Breslow, N.E. 1996. Statistics in epidemiology: the case-control study. Journal of the American Statistical Association, 91 CrossRef | Google Scholar | PubMed, 14–28. (Cited on p. 29.)
Breslow, N.E. and Cain, K.C. 1988. Logistic regression for two-stage case-control data. Biometrika, 75 CrossRef | Google Scholar, 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 Google Scholar, 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 Google Scholar: 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 943–952. (Cited on p. 61.)
Breslow, N.E. and Powers, W. 1978. Are there two logistic regressions for retrospective studies?Biometrics, 34 CrossRef | Google Scholar | PubMed, 100–105. (Cited on p. 108.)
Breslow, N.E. and Zhao, L.P. 1988. Logistic regression for stratified case-control studies. Biometrics, 44 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 71–78. (Cited on p. 130.)
Buonaccorsi, J.P. 2010. Measurement Error. Models, Methods and Applications CrossRef | Google Scholar. 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar. 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 994–1003. (Cited on p. 236.)
Cochran, W.G. 1954. The combination of estimates from different experiments. Biometrics, 10 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 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 Google Scholar, 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 CrossRef | Google Scholar, 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 Google Scholar, 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 Google Scholar, 215–242. (Cited on p. 61.)
Cox, D.R. 1958b. Two further applications of a model for binary regression. Biometrika, 45 CrossRef | Google Scholar, 562–565. (Cited on p. 82.)
Cox, D.R. 1961. Tests of separate families of hypotheses, in Proc. 4th Berkeley Symp., 1 Google Scholar, 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 Google Scholar, 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 Google Scholar: Wiley. (Cited on p. 238.)
Cox, D.R. 1972. Regression models and life tables. Journal of the Royal Statistical Society Series B, 34 Google Scholar, 187–202. (Cited on pp. 186 and 189.)
Cox, D.R. 1975. Partial likelihood. Biometrika, 62 CrossRef | Google Scholar, 269–276. (Cited on p. 186.)
Cox, D.R. 2006. Principles of Statistical Inference. Cambridge CrossRef | Google Scholar: Cambridge University Press. (Cited on p. 261.)
Cox, D.R. and Lewis, P.A.W. 1966. The Statistical Analysis of Series of Events. London CrossRef | Google Scholar: Methuen. (Cited on p. 131.)
Cox, D.R. and Oakes, D. 1984. Analysis of Survival Data. London Google Scholar: Chapman and Hall. (Cited on p. 187.)
Cox, D.R. and Snell, E.J. 1989. Analysis of Binary Data. 2nd edn. London Google Scholar: 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 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 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 Google Scholar | PubMed (Suppl. 1), 95–103. (Cited on p. 185.)
De Stavola, B.L. and Cox, D.R. 2008. On the consequences of overstratification. Biometrika, 95 CrossRef | Google Scholar, 992–996. (Cited on p. 109.)
DerSimonian, R. and Laird, N. 1986. Meta-analysis in clinical trials. Controlled Clinical Trials, 7 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 739–748. (Cited on p. 26.)
Domowitz, I. and Sartain, R.L. 1999. Determinants of the consumer bankruptcy decision. Journal of Finance, 54 CrossRef | Google Scholar, 403–420. (Cited on p. 28.)
Drescher, K. and Schill, W. 1991. Attributable risk estimation from case-control data via logistic regression. Biometrics, 47 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 712–717. (Cited on p. 236.)
Dupont, W.D. 1988. Power calculations for matched case-control studies. Biometrics, 44 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 27–32. (Cited on pp. 30 and 108.)
Farrington, C.P. 1995. Relative incidence estimation from case series for vaccine safety evaluation. Biometrics, 51 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 128–134. (Cited on p. 109.)
Firth, D. and de Menezes, R.X. 2004. Quasi-variances. Biometrika, 91 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 87–94. (Cited on p. 60.)
Fisher, R.A. 1935. The logic of inductive inference (with discussion). Journal of the Royal Statistical Society, 98 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 5195–5216. (Cited on p. 238.)
Gail, M.H. 1998. Case-control study, hospital-based, in Encyclopedia of Biostatistics, Volume 1, p. 514. Chichester Google Scholar: 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 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 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 Google Scholar, 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 Google Scholar | PubMed, 1004–1013. (Cited on p. 131.)
Godambe, V.P. 1960. An optimum property of regular maximum likelihood estimation. Annals of Mathematical Statistics, 31 CrossRef | Google Scholar, 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 Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 2078–2086. (Cited on p. 95.)
Greenland, S. 1982. The effect of misclassification in matched-pair case-control studies. American Journal of Epidemiology, 116 CrossRef | Google Scholar | PubMed, 402–406. (Cited on p. 237.)
Greenland, S. 1986. Adjustment of risk ratios in case-base studies (hybrid epidemiologic designs). Statistics in Medicine, 5 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 547–553. (Cited on pp. 30 and 61.)
Greenland, S., Pearl, J., and Robins, J.M. 1999. Causal diagrams for epidemiologic research. Epidemiology, 10 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 3755–3775. (Cited on p. 239.)
Gustafson, P. 2003. Measurement Error and Misclassification in Statistics and Epidemiology CrossRef | Google Scholar. 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 1225–1234. (Cited on pp. 138 and 158.)
Hedges, L.V. and Olkin, I. 1985. Statistical Methods for Meta-Analyses. San Diego, Calif. Google Scholar: 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 Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 1158–1160. (Cited on p. 251.)
Higgins, J.P. and Thompson, S.G. 2002. Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 219–220. (Cited on p. 251.)
Hughes, M.D. 1993. Regression dilution in the proportional hazards model. Biometrics, 49 CrossRef | Google Scholar | PubMed, 1056–1066. (Cited on p. 238.)
Hui, S.L. and Walter, S.D. 1980. Estimating the error rates of diagnostic tests. Biometrics, 36 CrossRef | Google Scholar | PubMed, 167–171. (Cited on p. 236.)
Jackson, M. 2009. Disadvantaged through discrimination? The role of employers in social stratification. British Journal of Sociology, 60 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed (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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 207–213. (Cited on p. 131.)
King, G. and Zeng, L. 2001a. Explaining rare events in international relations. International Organization, 55 CrossRef | Google Scholar, 693–715. (Cited on p. 30.)
King, G. and Zeng, L. 2001b. Improving forecasts of state failure. World Politics, 53 CrossRef | Google Scholar, 623–658. (Cited on p. 28.)
King, G. and Zeng, L. 2001c. Logistic regression in rare events data. Political Analysis, 9 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar, 1135–1148. (Cited on p. 238.)
Kuha, J. and Skinner, C. 1997. Survey Measurement and Process Quality. New York Google Scholar: 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 Google Scholar: 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 CrossRef | Google Scholar, 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 Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 324–328. (Cited on p. 110.)
Kuritz, S.J. and Landis, J.R. 1988a. Attributable risk estimation from matched case-control data. Biometrics, 44 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 507–517. (Cited on p. 109.)
Langholz, B. 2010. Case-control studies = odds ratios: blame the retrospective model. Epidemiology, 21 CrossRef | Google Scholar | PubMed, 10–12. (Cited on p. 30.)
Langholz, B. and Borgan, Ø. 1995. Counter-matching: a stratified nested case-control sampling method. Biometrika, 82 CrossRef | Google Scholar, 69–79. (Cited on p. 187.)
Langholz, B. and Borgan, Ø. 1997. Estimation of absolute risk from nested case-control data. Biometrics, 53 CrossRef | Google Scholar | PubMed, 767–774. (Cited on p. 189.)
Langholz, B. and Clayton, D. 1994. Sampling strategies in nested case-control studies. Environmental Health Perspectives, 102 CrossRef | Google Scholar | PubMed (Suppl. 8), 47–51. (Cited on p. 187.)
Langholz, B. and Goldstein, L. 1996. Risk set sampling in epidemiological cohort studies. Statistical Science, 11 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 169–176. (Cited on p. 211.)
Langholz, B. and Thomas, D.C. 1991. Efficiency of cohort sampling designs: some surprising results. Biometrics, 47 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 1341–1349. (Cited on p. 210.)
Liu, I.-M. and Agresti, A. 1996. Mantel-Haenszel-type inference for cumulative log odds ratios. Biometrics, 52 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 144–153. (Cited on p. 131.)
Manski, C.F. and McFadden, D.L. 1981. Structural Analysis of Discrete Data and Econometric Applications. Cambridge, Mass. Google Scholar: 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 CrossRef | Google Scholar | PubMed, 860–869. (Cited on p. 7.)
Mantel, N. 1966. Models for complex contingency tables and polychotomous dosage response curves. Biometrics, 22 CrossRef | Google Scholar | PubMed, 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 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 199–202. (Cited on p. 61.)
Maraganore, D. 2005. Blood is thicker than water: the strengths of family-based case-control studies. Neurology, 64 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 337–344. (Cited on p. 130.)
Marti, H. and Chavance, M. 2011. Multiple imputation analysis of case-cohort studies. Statistics in Medicine, 30 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar | PubMed, 271–287. (Cited on p. 251.)
McCullagh, P. 1980. Regression models for ordinal data (with discussion). Journal of the Royal Statistical Society B, 42 Google Scholar, 109–142. (Cited on p. 131.)
McNemar, Q. 1947. Note on the sampling error of the differences between correlated proportions or percentages. Psychometrika, 12 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 339–355. (Cited on p. 82.)
Miettinen, O.S. 1970. Matching and design efficiency in retrospective studies. American Journal of Epidemiology, 91 CrossRef | Google Scholar | PubMed, 111–118. (Cited on p. 82.)
Miettinen, O.S. 1976. Estimability and estimation in case-referent studies. American Journal of Epidemiology, 103 CrossRef | Google Scholar | PubMed, 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 Google Scholar | PubMed (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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 523–537. (Cited on p. 238.)
Nan, B. 2004. Efficient estimation for case-cohort studies. The Canadian Journal of Statistics, 32 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 993–1004. (Cited on p. 109.)
Neyman, J. and Scott, E.L. 1948. Consistent estimates based on partially consistent observations. Econometrica, 16 CrossRef | Google Scholar, 1–32. (Cited on p. 82.)
Nurminen, M. 1989. Analysis of epidemiologic case-base studies for binary data. Statistics in Medicine, 8 CrossRef | Google Scholar | PubMed, 1241–1254. (Cited on p. 209.)
Oakes, D. 1981. Survival times: aspects of partial likelihood. International Statistical Review, 49 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 89–95. (Cited on p. 82.)
Prentice, R.L. 1976. Use of the logistic model in retrospective studies. Biometrics, 32 CrossRef | Google Scholar | PubMed, 599–606. (Cited on p. 108.)
Prentice, R.L. 1982. Covariate measurement errors and parameter estimation in a failure time regression model. Biometrika, 69 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 1–11. (Cited on pp. 209 and 210.)
Prentice, R.L. 1986b. On the design of synthetic case-control studies. Biometrics, 42 CrossRef | Google Scholar | PubMed, 301–310. (Cited on p. 187.)
Prentice, R.L. and Breslow, N.E. 1978. Retrospective studies and failure time models. Biometrika, 65 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar: 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 1400–1413. (Cited on p. 238.)
Rothman, K.J., Greenland, S., and Lash, T.L. 2008. Modern Epidemiology. 3rd edn. Philadelphia Google Scholar: Lippincott Williams & Wilkins. (Cited on pp. 30 and 209.)
Rubin, D.B. 1987. Multiple Imputation for Nonresponse in Surveys. New York CrossRef | Google Scholar: 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 976–985. (Cited on p. 29.)
Samuelsen, S.O. 1997. A pseudolikelihood approach to analysis of nested case-control studies. Biometrika, 84 CrossRef | Google Scholar, 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 CrossRef | Google Scholar (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 CrossRef | Google Scholar, 1215–1221. (Cited on p. 209.)
Sato, T. 1994. Risk ratio estimation in case-cohort studies. Environmental Health Perspectives, 102 CrossRef | Google Scholar | PubMed (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 CrossRef | Google Scholar | PubMed. (Cited on p. 158.)
Schaid, D.J. 1999. Case-parents design for gene-environment interaction. Genetic Epidemiology, 16 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 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 Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 1179S–1186S. (Cited on p. 238.)
Steenland, K. and Deddens, J.A. 1997. Increased precision using countermatching in nested case-control studies. Epidemiology, 8 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 261. (Cited on p. 189.)
Stuart, E. 2010. Matching methods for causal inference. Statistical Science, 25 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed. (Cited on p. 158.)
Sutton, A.J. and Higgins, J.P.T. 2008. Recent developments in meta-analysis. Statistics in Medicine, 27 CrossRef | Google Scholar | PubMed, 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 Google Scholar. (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 Google Scholar, 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 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 2693–2708. (Cited on p. 251.)
Thompson, S.K. 1992. Sampling. New York Google Scholar | PubMed: 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 Google Scholar: 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 CrossRef | Google Scholar, 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 Google Scholar | PubMed, 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 Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 119–128. (Cited on p. 157.)
Whittemore, A.S. 1982. Statistical methods for estimating attributable risk from retrospective data. Statistics in Medicine, 1 CrossRef | Google Scholar | PubMed, 229–243. (Cited on p. 110.)
Whittemore, A.S. 1995. Logistic regression of family data from case-control studies. Biometrika, 82 CrossRef | Google Scholar, 57–67. (Cited on p. 158.)
Whittemore, A.S. and Halpern, J. 1989. Testing odds-ratio equality for several diseases. Statistics in Medicine, 76 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar | PubMed, 177–189. (Cited on pp. 158 and 159.)
Wild, C.J. 1991. Fitting prospective regression models to case-control data. Biometrika, 78 CrossRef | Google Scholar, 705–717. (Cited on pp. 131, 157 and 158.)
Willett, W. 1998. Nutritional Epidemiology CrossRef | Google Scholar. 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 CrossRef | Google Scholar | PubMed, 694–705. (Cited on p. 158.)
Woolf, B. 1955. On estimating the relationship between blood group and disease. Annals of Human Genetics, 19 CrossRef | Google Scholar, 251–253. (Cited on p. 61.)
Wright, S. 1921. Correlation and causation. Journal of Agricultural Research, 20 Google Scholar, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 1179–1189. (Cited on p. 112.)
Yates, F. and Cochran, W.G. 1938. The analysis of groups of experiments. Journal of Agricultural Science, 28 Google Scholar, 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 CrossRef | Google Scholar | PubMed, 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 CrossRef | Google Scholar, 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 CrossRef | Google Scholar, 299–315. (Cited on p. 159.)
Zhou, H. and Pepe, M.S. 1995. Auxiliary covariate data in failure time regression. Biometrika, 82 CrossRef | Google Scholar, 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 CrossRef | Google Scholar | PubMed, doi:10.1186/1476-069X-9-40. (Cited on p. 213.)

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 6488 *
Loading metrics...

Book summary page views

Total views: 19141 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 15th April 2025. This data will be updated every 24 hours.

Usage data cannot currently be displayed.