References
Methodology related to the analysis of observational
studies:
Baker SG, Lindeman KL, and Kramer, BS The paired
availability design for historical controls BMC Medical Research Methodology
2001, 1:9. http://www.biomedcentral.com/1471-2288/1/9
Rubin DB Estimating causal effects from large data sets
using propensity scores ANN INTERN MED 127 (8): 757-763 Part 2 OCT 15 1997
Baker, SG and Lindeman, K.L. Rethinking historical
controls. Biostatistics 2001,2: 383-396. [Some of this is a bit technical, but
it includes a comparison of results from paired availability design, propensity
score, and a meta-analysis of randomized trials]
Baker SG and Kramer, BS Good for women, good for men,
bad for people: Simpson's paradox and the importance of sex-specific analysis
in observational studies. Journal of Women's Health & Gender-Based Medicine
2001, 10, 867 - 872. [Graphical view of Simpson's Paradox]
Methodology related to randomized trials
Baker SG and Kramer BS The transitive fallacy for
randomized trials: If A bests B and B bests C in separate trials, is A better
than C? BMC Medical Research Methodology 2002, BMC Medical Research Methodology
2002, 2:13 http://www.biomedcentral.com/1471-2288/2/13
Baker SG and Kramer BS. Randomized trials,
generalizability, and meta-analysis: Graphical insights for binary outcomes.
BMC Medical Research Methodology 2003, 3:10
http://www.biomedcentral.com/1471-2288/3/10
The fallacy of enrolling only high-risk subjects in
cancer prevention trials: Is there a "free lunch"?
Stuart G Baker, Barnett S Kramer and Donald Corle BMC
Medical Research Methodology 2004, 4:24 (04 Oct 2004)
http://www.biomedcentral.com/1471-2288/4/24
Moses LE, Mosteller F, Buehler JH Comparing results of
large clinical trials to those of meta-analyses Statistics In Medicine 21 (6):
793-800 MAR 30 2002
Baker, SG and Freedman LS. A simple method for analyzing
data from a randomized trial with a missing binary outcome. BMC Medical
Research Methodology 2003, 3:8
http://www.biomedcentral.com/1471-2288/3/8
Correction: http://www.biomedcentral.com/1471-2288/4/1
Methodology related to surrogate endpoints
Baker SG and Kramer BS. A perfect correlate does not a
surrogate make BMC Medical Research Methodology 2003, 3:16
http://www.biomedcentral.com/1471-2288/3/16
Methodology for evaluating cancer screening
Baker SG, Kramer BS, and Prorok, PC. Statistical issues
in randomized trials of cancer screening. BMC Medical Research Methodology
2002, 2:11 http://www.biomedcentral.com/1471-2288/2/11
[Cancer screening trials require special analytic techniques]
Baker SG, Erwin D, Kramer BS, Prorok, PC. Using
observational data to estimate an upper bound on the reduction in cancer
mortality due to periodic screening, BMC Medical Research Methodology 2003, 3:4
(06 Mar 2003) http://www.biomedcentral.com/1471-2288/3/4
Baker SG, Kramer BS, and Prorok PC. Comparing cancer
mortality rates before-and-after a change in availability of screening in
different regions: Extension of the paired availability design. BMC Medical
Research Methodology 2004, 4:12.
http://www.biomedcentral.com/1471-2288/4/12
Baker SG and Kramer BS. Estimating the Cumulative Risk
of False Positive Cancer Screenings. BMC Medical Research Methodology 2003,
3:11http://www.biomedcentral.com/1471-2288/3/11
Methodology related to validation of biomarkers
Baker SG, Kramer, BS and Srivastava, S. Markers for
early detection of cancer: Statistical issues for nested case-control studies.
BMC Medical Research Methodology 2002, 2:4,
http://www.biomedcentral.com/1471-2288/2/4/.
Baker SG, Kramer BS, and Prorok PC. Development tracks
for cancer prevention markers. Disease Markers 2004, 20:97-102
Baker SG. Kramer BS. Biomarkers, surrogate endpoints,
and early detection imaging tests: reducing confusion. International Chinese
Statistical Association Bulletin. January 2004
http://www.icsa.org/bulletin/Bulletin-1-2004-Contents/A3-25-controverstial-issues-v4.doc
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