A simple meta-analytic approach for using a binary surrogate endpoint to predict the effect of intervention on true endpoint
Author:
Publisher
Oxford University Press (OUP)
Subject
Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability
Link
http://academic.oup.com/biostatistics/article-pdf/7/1/58/669410/kxi040.pdf
Reference23 articles.
1. BAKER, S. G., IZMIRLIAN, G. AND KIPNIS, V. (2005). Resolving paradoxes involving surrogate endpoints. Journal of the Royal Statistical Society, Series A. doi:10.1111/j.1467-985X.2005.00373.x.
2. BAKER, S. G. AND KRAMER, B. S. (2003). A perfect correlate does not a surrogate make. BMC Medical Research Methodology3, 16.
3. BAKER, S. G. AND KRAMER, B. S. (2005). Simple maximum likelihood estimates of efficacy in randomized trials and before-and-after studies, with implications for meta-analysis. Statistical Methods in Medical Research14, 349–367.
4. BEGG, C. B. AND LEUNG, D. H. Y. (2000). On the use of surrogate endpoints in randomized trials (with discussion). Journal of the Royal Statistical Society, Series A163, 15–28.
5. BURZYKOWSKI, T., MOLENBERGHS, G. AND BUYSE, M. (2004). The validation of surrogate endpoints using data from randomized clinical trials: a case-study in advanced colorectal cancer. Journal of the Royal Statistical Society, Series A167, 103–124.
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