Abstract
A fundamental challenge pervasive to all experimental and nonexperimental (observational) research is valid inference of causal effects. Although actions (through undefined mechanisms, but conventionally denoted by treatment, exposure, etc.) and reactions (e.g., disease, remission, cure) must occur by definition in individuals, the realm of epidemiology principally lies in the study of individuals in the aggregate, such as patients enrolled in clinical trials, participants in cohorts, and populations. Until recently, advancements in epidemiological methods developed in the last half-century have hence largely fallen into the domain of the two major observational study designs used: cohort and case-control studies (cf. Chap. I.5 and I.6 of this handbook).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Barlow WE, Ichikawa L, Rosner D, Izumi S (1999) Analysis of case-cohort designs. J Clin Epidemiol 52:1165–1172
Begg CB, Zhang ZF (1994) Statistical analysis of molecular epidemiology studies employing case series. Cancer Epidemiol Biomarkers Prev 3:173–175
Cornfield J (1951) A method of estimating comparative rates from clinical data. JNCI 11:1269–1275
Ellsworth DL, Manolio TA (1999) The emerging importance of genetics in epidemiologic research. I. Basic concepts in human genetics and laboratory technology. Ann Epidemiol 9:1–16
Garcia-Closas M, Thompson WD, Robins JM (1998) Differential misclassification and the assessment of gene-environment interactions in case-control studies. Am J Epidemiol 147:426–433
Greenland S (1982) The effect of misclassification in matched-pair case-control studies. Am J Epidemiol 116:402–406
Greenland S (1996) Confounding and exposure trends in case-crossover and case-time-control designs. Epidemiol 7:231–239
Greenland S (1999) A unified approach to the analysis of case-distribution (caseonly) studies. Stat Med 18:1–15
Greenland S, Thomas DC (1982) On the need for the rare disease assumption in case-control studies. Am J Epidemiol 116:547–553
Greenland S, Robins JM (1985) Estimation of a common effect parameter from sparse follow-up data. Biometrics 41:55–68
Kelsey JL, Whittemore AS, Evans AS, Thompson WD (1996) Methods in Observational Epidemiology, second edition. Oxford University Press, New York, pp 122–125
Khoury MJ (1997) Genetic epidemiology and the future of disease prevention and public health. Epidemiol Rev 19:175–180
Kupper LL, McMichael AJ, Spirtas R (1975) A hybrid epidemiologic study design useful for estimating relative risk. J Am Stat Assoc 70:524–528
Langholz B, Thomas DC (1990) Nested case-control and case-cohort methods of sampling from a cohort: a critical comparison. Am J Epidemiol 131:169–176
Little RJ, Rubin DR (2000) Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches. Annu Rev Public Health 21:121–145
Maclure M (1991) The case-crossover design: a method for studying transient effects on the risk of acute events. Am J Epidemiol 133:144–153
Maclure M, Mittleman MA (2000) Should we use a case-crossover design? Annu Rev Public Health 21:193–221
Miettinen OS (1976) Estimability and estimation in case-referent studies. Am J Epidemiol 103:226–235
Miettinen OS (1982) Design options in epidemiologic research: an update. Scand J Work Environ Health 8(Suppl 1):7–14
Mittleman MA, Maclure M, Robins JM (1995) Control sampling strategies for case-crossover studies: an assessment of relative efficiency. Am J Epidemiol 142:91–98
Navidi W (1998) Bidirectional case-crossover designs for exposures with time trends. Biometrics 54:596–605
Navidi W, Weinhandl E (2002) Risk set sampling for case-crossover designs. Epidemiol 13:100–105
Prentice RL (1986) A case-cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika 73:1–11
Redelmeier DA, Tibshirani RJ (1997) Interpretation and bias in case-crossover studies. J Clin Epidemiol 50:1281–1287
Sato T (1992a) Maximum likelihood estimation of the risk ratio in case-cohort studies. Biometrics 48:1215–1221
Sato T (1992b) Estimation of a common risk ratio in stratified case-cohort studies. Stat Med 11:1599–1605
Suissa S (1995) The case-time-control study. Epidemiol 6:248–253
Suissa S (1998) The case-time-control design: further assumptions and conditions. Epidemiol 9:441–445
Szklo M, Nieto J (2000) Epidemiology: Beyond the basics. Aspen Publishers, Gaithersburg, MD, pp 33–38
Vines SK, Farrington CP (2001) Within-subject exposure dependency in case-crossover studies. Stat Med 20:3039–3049
Wacholder S (1991) Practical considerations in choosing between case-cohort and nested case-control designs. Epidemiol 2:155–158
Wacholder S, Boivin JF (1987) External comparisons with the case-cohort design. Am J Epidemiol 126:1198–1209
Wertheimer N, Leeper E (1979) Electrical wiring configurations and childhood cancer. Am J Epidemiol 109:273–284
Wilcox AJ, Weinberg CR, Lie RT (1998) Distinguishing the effects of maternal and offspring genes through studies of “case-parent triads”. Am J Epidemiol 148:893–901
Yang Q, Khoury MJ (1997) Evolving methods in genetic epidemiology. III. Gene-environment interaction in epidemiologic research. Epidemiol Rev 19:33–43
Yang Q, Khoury MJ, Flanders WD (1997) Sample size requirements in case-only designs to detect gene-environment interaction. Am J Epidemiol 146:713–720
Zaffanella LE, Savitz DA, Greenland S, Ebi KL (1998) The residential case-specular method to study wire codes, magnetic fields, and disease. Epidemiol 9:16–20
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Kass, P.H., Gold, E.B. (2005). Modern Epidemiologic Study Designs. In: Ahrens, W., Pigeot, I. (eds) Handbook of Epidemiology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-26577-1_8
Download citation
DOI: https://doi.org/10.1007/978-3-540-26577-1_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-00566-7
Online ISBN: 978-3-540-26577-1
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)