Sage Journals: Discover world-class research

Abstract

One feature of the Bayesian approach is that it provides methods for synthesizing what is known about a question of interest and provides a formalism based on the laws of probability for incorporating this auxiliary knowledge into the planning and the analysis of the next study. In this comment, we use elements of the Goodman-Sladky case study to illustrate (1) the use of Bayesian methods to quantify historical information about an intervention through the specification of a prior distribution, (2) an approach to the analysis of the sensitivity of the conclusions of a Bayesian analysis to the specification of the prior distribution, and (3) we comment on the role of research synthesis for combining information about an intervention from different data sources as a tool to help summarize evidence about the intervention.

Get full access to this article

View all access options for this article.

References

1. Van der Merche FGA, Schmitz PIM and the Dutch Guillain-Barré Study Group . A randomized trial comparing intravenous immune globulin and plasma exchange in Guillain-Barré Syndrome. New Engl J Med 1992; 326: 1123–1129.

2. Guillain-Barré Syndrome Trial Group . Randomized trial of plasma exchange, intravenous immunoglobulin, and combined treatments in Guillain-Barré Syndrome. Lancet 1997; 349: 225–230.

3. Kass R , Greenhouse J. Comment on “Investigating therapies of potentially great benefit: ECMO” by J. Ware. Statist Sci 1989; 4: 31–37.

4. Spiegelhalter DJ , Abrams KR , Myles JP. Bayesian approaches to clinical trials and health-care evaluation. Chichester, England: John Wiley & Sons, 2004.

5. Tsiatis AA . The asymptotic joint distribution of the efficient scores test for the proportional hazards model calculated over time. Biometrika 1981; 68: 311–315.

6. Edwards W , Lindman H , Savage L. Bayesian statistical inference for psychological research. Psychol Rev 1963; 70: 193–242.

7. Greenhouse J , Wasserman L. Robust Bayesian analysis of clinical trials. Statist Med 1995; 14: 1379–1391.

8. Seltman H , Greenhouse J , Wasserman L. Bayesian model selection: analysis of a survival model with a surviving fraction. Statist Med 2001; 20: 1681–1691.

9. Huber PJ. The use of Choquet capacities in statistics. Bull. Int. Statist Inst 1973; 45: 181–191.

10.

10. Berger J. The robust Bayesian viewpoint (with discussion). In Kadane J ed. Robustness in Bayesian statistics. Amsterdam: North-Holland, 1984, 63–124.

11.

11. Berger J , Berliner LM. Robust Bayes and empirical Bayes analysis with 1-contaminated priors. Annals Statist 1986; 14: 461–486.

12.

12. Lavine M , Wasserman L , Wolpert R. Bayesian inference with specified prior marginals. J Am Statist Assoc 1991; 86: 964–971.

13.

13. Gaver DP , Draper D , Goel PK et al. Combining information: statistical issues and opportunities for research. Washington, DC: National Academy Press, 1992.

14.

14. DuMouchel W , Harris JE. Bayes methods for combining the results of cancer studies in humans and other species (with comment). J Am Statist Assoc 1983; 78: 293–308.

15.

15. Rubin DB.

Meta-analysis: literature synthesis or effect-size surface estimation?

J. Educ Statist 1992; 17: 363–374.

16.

16. Prevost TC , Abrams KR , Jones DR. Hierarchical models in generalized synthesis of evidence: an example based on studies of breast cancer screening. Statist Med 2000; 19: 3359–3376.

17.

17. Eddy DM , Hasselblad V , Schachter R. Meta-analysis by the confidence profile method. Boston: Academic Press, Inc., 1992.

18.

18. Droitcour J , Silberman G , Chelimsky E. Cross-design synthesis: a new form of meta-analysis for combining results from randomized clinical trials and medical-practice databases. Int J Technol Assess Health Care 1993; 9: 440–449.

19.

19. General Accounting Office Cross-design synthesis: a new strategy for medical effectiveness research. Washington, DC: General Accounting Office, 1992.

20.

20. Greenhouse SW , Greenhouse J. Jerome Cornfield. In Armitage P , Colton T eds. The encyclopedia of biostatistics. New York: John Wiley, 1998: 955–959.

21.

21. Cornfield J. Principles of research. Am J Mental Defic 1959, 64: 240–252.

Using prior distributions to synthesize historical evidence: comments on the Goodman–Sladky case study of IVIg in Guillain–Barré syndrome

Abstract

Get full access to this article

References