Skip to main content
SpringerLink
Log in

Modern Epidemiological Study Designs

  • Reference work entry
Handbook of Epidemiology

Abstract

A fundamental challenge pervasive to all experimental and non-experimental (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 at risk in cohorts, and populations. Until recently, innovations in epidemiological study design 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. chapters. Cohort Studies and Case-Control Studies of this handbook).

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 999.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 1,399.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  • Allard R (1998) The residential case-specular method to study wire codes, magnetic fields, and disease. Epidemiology 9:475–476

    Article  PubMed  CAS  Google Scholar 

  • Barlow WE, Ichikawa L, Rosner D, Izumi S (1999) Analysis of case-cohort designs. J Clin Epidemiol 52:1165–1172

    Article  PubMed  CAS  Google Scholar 

  • Bateson TF, Schwartz J (1999) Control for seasonal variation and time trend in case-crossover studies of acute effects of environmental exposures. Epidemiology 10:539–544

    Article  PubMed  CAS  Google Scholar 

  • Breslow NE, Chatterjee N (1999) Design and analysis of two-phase studies with binary outcome applied to Wilms tumour prognosis. Appl Stat 48:457–468

    Google Scholar 

  • Breslow N, Day NE (1987) Statistical methods in cancer research, volume II: The design and analysis of cohort studies. International Agency for Research on Cancer, Lyon

    Google Scholar 

  • Breslow NE, Lubin H, Marek P, Langholz B (1983) Multiplicative models and cohort analysis. J Am Stat Assoc 78:1–12

    Article  Google Scholar 

  • Breslow NE, Lumley T, Ballantyne CM, Chambless LE, Kulich M (2009a) Using the whole cohort in the analysis of case-cohort data. Am J Epidemiol 169:1398–1405

    Article  PubMed Central  PubMed  Google Scholar 

  • Breslow NE, Lumley T, Ballantyne CM, Chambless LE, Kulich M (2009b) Improved Horvitz-Thompson estimation of model parameters from two-phase stratified samples: applications in epidemiology. Stat Biosci 1:32

    Article  PubMed Central  PubMed  Google Scholar 

  • Cornfield J (1951) A method of estimating comparative rates from clinical data. J Natl Cancer Inst 11:1269–1275

    PubMed  CAS  Google Scholar 

  • D’Angio GJ, Breslow N, Beckwith B, Evans A, Baum E, Delorimier A, Fernbach D, Hrabovsky E, Jones B, Kelalis P, Othersen B, Teft M, Thomas PRM (1989) Treatment of Wilms’ tumor. Cancer 64:349–360

    Article  PubMed  Google Scholar 

  • Deville JC, Särndal CE (1992) Calibration estimator in survey sampling. J Am Stat Assoc 87: 376–382

    Article  Google Scholar 

  • Ebi KL, Zaffanella LE, Greenland S (1999) Application of the case-specular method to two studies of wire codes and childhood cancers. Epidemiology 10:398–404

    Article  PubMed  CAS  Google Scholar 

  • Farrington CP (1995) Relative incidence estimation from case series for vaccine safety evaluation. Biometrics 31:228–235

    Article  Google Scholar 

  • Farrington CP (2004) Control without separate controls: evaluation of vaccine safety using case-only methods. Vaccine 22:2064–2070

    Article  PubMed  CAS  Google Scholar 

  • Farrington CP, Whitaker HJ (2006a) Semiparametric analysis of case series data. J R Stat Soc 55:553–594

    Article  Google Scholar 

  • Farrington CP, Whitaker HJ (2006b) Semiparametric analysis of case series data. Appl Stat 55: 553–594

    Google Scholar 

  • Greenland S (1996) Confounding and exposure trends in case-crossover and case-time-control designs. Epidemiology 7:231–239

    Article  PubMed  CAS  Google Scholar 

  • Greenland S (1999) A unified approach to the analysis of case-distribution (case-only) studies. Stat Med 18:1–15

    Article  PubMed  CAS  Google Scholar 

  • Greenland S, Robins JM (1985) Estimation of a common effect parameter from sparse follow-up data. Biometrics 41:55–68

    Article  PubMed  CAS  Google Scholar 

  • Greenland S, Thomas DC (1982) On the need for the rare disease assumption in case-control studies. Am J Epidemiol 116:547–553

    PubMed  CAS  Google Scholar 

  • Greenland S, Thomas DC, Morgenstern H (1986) The rare-disease assumption revisited. A critique of “estimators of relative risk for case-control studies”. Am J Epidemiol 124:869–883

    PubMed  CAS  Google Scholar 

  • Janes H, Sheppard L, Lumley T (2005a) Case-crossover analyses of air pollution exposure data: referent selection strategies and their implications for bias. Epidemiology 16:717–726

    Article  PubMed  Google Scholar 

  • Janes H, Sheppard L, Lumley T (2005b) Overlap bias in the case-crossover design, with application to air pollution exposures. Stat Med 24:285–300

    Article  PubMed  Google Scholar 

  • Kulich M, Lin DY (2004) Improving the efficiency of relative-risk estimation in case-cohort studies. J Am Stat Assoc 99:832–844

    Article  Google Scholar 

  • Kupper LL, McMichael AJ, Spirtas R (1975) A hybrid epidemiologic study design useful for estimating relative risk. J Am Stat Assoc 70:524–528

    Google Scholar 

  • L’Abbé KA, Howe GR, Burch JD, Miller AB, Abbatt J, Band P, Choi W, Du J, Feather J, Gallagher R, Hill G, Matthews V (1991) Radon exposure, cigarette smoking, and other mining experience in the Beaverlodge uranium miners cohort. Health Phys 60:489–495

    Article  PubMed  Google Scholar 

  • Langholz B (2005) Counter-matching. In: Armitage P, Colton T (eds) Encyclopedia of biostatistics, 2nd edn. Wiley, Chichester

    Google Scholar 

  • Langholz B, Borgan Ø (1995) Counter-matching: a stratified nested case-control sampling method. Biometrika 82:69–79

    Article  Google Scholar 

  • Langholz B, Clayton D (1994) Sampling strategies in nested case-control studies. Environ Health Perspect 102(Suppl 8):47–51

    Article  PubMed Central  PubMed  Google Scholar 

  • 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

    PubMed  CAS  Google Scholar 

  • Lin DY, Ying Z (1993) Cox regression with incomplete covariate measurements. J Am Stat Assoc 88:1341–1349

    Article  Google Scholar 

  • 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

    Article  PubMed  CAS  Google Scholar 

  • Lumley T (2008) Analysis of complex samples in R. Surv Stat 57:20–25

    Google Scholar 

  • Lumley T, Levy D (2000) Bias in the case-crossover design: implications for studies of air pollution. Environmetrics 11:689–704

    Article  CAS  Google Scholar 

  • 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

    PubMed  CAS  Google Scholar 

  • Mark SD, Katki HA (2006) Specifying and implementing nonparametric and semiparametric survival estimators in two-stage (sampled) cohort studies with missing case data. J Am Stat Assoc 101:460–471

    Article  CAS  Google Scholar 

  • Miettinen OS (1976) Estimability and estimation in case-referent studies. Am J Epidemiol 103:226–235

    PubMed  CAS  Google Scholar 

  • Miettinen OS (1982) Design options in epidemiologic research: an update. Scand J Work Environ Health 8(Suppl 1):7–14

    PubMed  Google Scholar 

  • 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

    PubMed  CAS  Google Scholar 

  • Musonda P, Farrington CP, Whitaker HJ (2006) Sample sizes for self-controlled case series studies. Stat Med 25:2618–2631. Erratum in: Statistics in Medicine 2008 27:4854–4855

    Article  PubMed  Google Scholar 

  • Navidi W (1998) Bidirectional case-crossover designs for exposures with time trends. Biometrics 54:596–605

    Article  PubMed  CAS  Google Scholar 

  • Navidi W, Weinhandl E (2002) Risk set sampling for case-crossover designs. Epidemiology 13:100–105

    Article  PubMed  Google Scholar 

  • Prentice RL (1986) A case-cohort design for epidemiologic cohort studies and disease prevention trials. Biometrika 73:1–11

    Article  Google Scholar 

  • Robins JM, Rotnitzky A, Zhao LP (1994) Estimation of regression coefficients when some regressors are not always observed. J Am Stat Assoc 89:846–866

    Article  Google Scholar 

  • Sato T (1992a) Maximum likelihood estimation of the risk ratio in case-cohort studies. Biometrics 48:1215–1221

    Article  Google Scholar 

  • Sato T (1992b) Estimation of a common risk ratio in stratified case-cohort studies. Stat Med 11:1599–1605

    Article  PubMed  CAS  Google Scholar 

  • Sato T (1994) Risk ratio estimation in case-cohort studies. Environ Health Perspect 102(Suppl 8):53–56

    Article  PubMed Central  PubMed  Google Scholar 

  • Steenland K, Deddens JA (1997) Increased precision using countermatching in nested case-control studies. Epidemiology 8:238–242

    Article  PubMed  CAS  Google Scholar 

  • Suissa S (1995) The case-time-control study. Epidemiology 6:248–253

    Article  PubMed  CAS  Google Scholar 

  • Suissa S (1998) The case-time-control design: further assumptions and conditions. Epidemiology 9:441–445

    Article  PubMed  CAS  Google Scholar 

  • Suissa S, Dell’Aniello S, Martinez C (2010) The multitime case-control design for time-varying exposures. Epidemiology 21:876–883

    Article  PubMed  Google Scholar 

  • The Atherosclerosis Risk in Communities (ARIC) study: design and objectives (1989) The ARIC Investigators. Am J Epidemiol 129:687–702

    Google Scholar 

  • Vines SK, Farrington CP (2001) Within-subject exposure dependency in case-crossover studies. Stat Med 20:3039–3049

    Article  PubMed  CAS  Google Scholar 

  • Wacholder S (1991) Practical considerations in choosing between case-cohort and nested case-control designs. Epidemiology 2:155–158

    Article  PubMed  CAS  Google Scholar 

  • Wacholder S, Boivin JF (1987) External comparisons with the case-cohort design. Am J Epidemiol 126:1198–1209

    PubMed  CAS  Google Scholar 

  • Walker AM (1982) Anamorphic analysis: sampling and estimation for covariate effects when both exposure and disease are known. Biometrics 38:1025–1032

    Article  PubMed  CAS  Google Scholar 

  • Wang S, Linkletter C, Maclure M, Dore D, Mor V, Buka S, Wellenius GA (2011) Future cases as present controls to adjust for exposure trend bias in case-only studies. Epidemiology 22: 568–574

    Article  PubMed Central  PubMed  Google Scholar 

  • Wertheimer N, Leeper E (1979) Electrical wiring configurations and childhood cancer. Am J Epidemiol 109:273–284

    PubMed  CAS  Google Scholar 

  • Whitaker HJ, Farrington CP, Spiessens B, Musonda P (2006) Tutorial in biostatistics: the self-controlled case series method. Stat Med 25:1768–1797s

    Article  PubMed  Google Scholar 

  • Whitaker HJ, Hocine MN, Farrington CP (2007) On case-crossover methods for environmental time series data. Environmetrics 18:157–171

    Article  CAS  Google Scholar 

  • Whitaker HJ, Hocine MN, Farrington CP (2009) The methodology of self-controlled case series studies. Stat Methods Med Res 18:7–26

    Article  PubMed  Google Scholar 

  • White JE (1982) A two stage design for the study of the relationship between a rare exposure and a rare disease. Ame J Epidemiol 115:119–128

    CAS  Google Scholar 

  • Witt MB (2009) Overview of software that will produce sample weight adjustments. Joint statistical meetings, section on survey research methods. http://www.amstat.org/sections/srms/Proceedings/y2009/Files/304290.pdf. Accessed 28 Nov 2011

  • Zaffanella LE, Savitz DA, Greenland S, Ebi KL (1998) The residential case-specular method to study wire codes, magnetic fields, and disease. Epidemiology 9:16–20

    Article  PubMed  CAS  Google Scholar 

  • Zhang H, Schaubel DE, Kalbfleisch JD (2011) Proportional hazards regression for the analysis of clustered survival data from case-cohort studies. Biometrics 67:18–28

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

I would like to gratefully acknowledge the invaluable advice of the anonymous reviewer of the first edition of this chapter, who suggested numerous additional references and topics deserving greater attention, in turn helping to greatly improve its second edition.

Author information

Authors and Affiliations

  1. Department of Population Health and Reproduction, University of California School of Veterinary Medicine, 95616, Davis, CA, USA

    Philip H. Kass

Authors
  1. Philip H. Kass
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Epidemiological Methods and Etiologic Research, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany

    Wolfgang Ahrens

  2. Department of Biometry and Data Management, Leibniz Institute for Prevention Research and Epidemiology – BIPS, Bremen, Germany

    Iris Pigeot

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this entry

Cite this entry

Kass, P.H. (2014). Modern Epidemiological Study Designs. In: Ahrens, W., Pigeot, I. (eds) Handbook of Epidemiology. Springer, New York, NY. https://doi.org/10.1007/978-0-387-09834-0_8

Download citation

  • DOI: https://doi.org/10.1007/978-0-387-09834-0_8

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-09833-3

  • Online ISBN: 978-0-387-09834-0

  • eBook Packages: MedicineReference Module Medicine

Publish with us

Policies and ethics

Search

Navigation