The International Journal of Biostatistics
Ed. by Chambaz, Antoine / Hubbard, Alan E. / van der Laan, Mark J.
2 Issues per year
IMPACT FACTOR 2014: 0.741
5-year IMPACT FACTOR: 1.475
SCImago Journal Rank (SJR) 2014: 1.247
Source Normalized Impact per Paper (SNIP) 2014: 1.078
Impact per Publication (IPP) 2014: 1.206
Mathematical Citation Quotient (MCQ) 2014: 0.07
Volume 7 (2011)
Volume 5 (2009)
Volume 4 (2008)
Volume 3 (2007)
Volume 2 (2006)
Volume 1 (2005)
Most Downloaded Articles
- Sample Size Estimation for Repeated Measures Analysis in Randomized Clinical Trials with Missing Data by Lu, Kaifeng/ Luo, Xiaohui and Chen, Pei-Yun
- An Introduction to Causal Inference by Pearl, Judea
- Survival Models in Health Economic Evaluations: Balancing Fit and Parsimony to Improve Prediction by Jackson, Christopher H/ Sharples, Linda D and Thompson, Simon G
- Survival Curve Estimation with Dependent Left Truncated Data Using Cox's Model by Mackenzie, Todd
- Evaluating treatment effectiveness in patient subgroups: a comparison of propensity score methods with an automated matching approach by Radice, Rosalba/ Ramsahai, Roland/ Grieve, Richard/ Kreif, Noemi/ Sadique, Zia and Sekhon, Jasjeet S.
Commentary on "Principal Stratification -- a Goal or a Tool?" by Judea Pearl
1Fred Hutchinson Cancer Research Center & University of Washington
2University of North Carolina at Chapel Hill
3University of Minnesota, Twin Cities
Citation Information: The International Journal of Biostatistics. Volume 7, Issue 1, Pages 1–15, ISSN (Online) 1557-4679, DOI: 10.2202/1557-4679.1341, September 2011
- Published Online:
This commentary takes up Pearl's welcome challenge to clearly articulate the scientific value of principal stratification estimands that we and colleagues have investigated, in the area of randomized placebo-controlled preventive vaccine efficacy trials, especially trials of HIV vaccines. After briefly arguing that certain principal stratification estimands for studying vaccine effects on post-infection outcomes are of genuine scientific interest, the bulk of our commentary argues that the “causal effect predictiveness” (CEP) principal stratification estimand for evaluating immune biomarkers as surrogate endpoints is not of ultimate scientific interest, because it evaluates surrogacy restricted to the setting of a particular vaccine efficacy trial, but is nevertheless useful for guiding the selection of primary immune biomarker endpoints in Phase I/II vaccine trials and for facilitating assessment of transportability/bridging surrogacy.
Here you can find all Crossref-listed publications in which this article is cited. If you would like to receive automatic email messages as soon as this article is cited in other publications, simply activate the “Citation Alert” on the top of this page.