[252] Parmigiani G, Ancukiewicz M, Matchar DB.
Decision models in clinical recommendations develop-
ment: the Stroke Prevention Policy Model
. In: Berry DA, Stangl DK, eds., Bayesian Biostatistics,
vol. 151 of Statistics: Textbooks and Monographs, 207–233. New York: Marcel Dekker 1996.
[253] Clyde MA, M¨
uller P, Parmigiani G.
Inference and design strategies for a hierarchical logistic
regression model
. In: Berry DA, Stangl DK, eds., Bayesian Biostatistics, vol. 151 of Statistics:
Textbooks and Monographs, 297–320. New York: Marcel Dekker 1996.
[254] Carota C, Parmigiani G.
On Bayes factors for nonparametric alternatives
. In: Bernardo JM,
Berger JO, Dawid AP, Smith AFM, eds., Bayesian Statistics 5 – Proceedings of the Fifth Valencia
International Meeting, 507–511. Clarendon Press [Oxford University Press] 1996.
[255] Clyde MA, Parmigiani G.
Orthogonalizations and priors for orthogonalized model mixing
. In:
Lee JC, Johnson WO, Zellner A, eds., Modelling and Prediction: Honoring of Seymour Geisser,
206–227. New York: Springer 1996.
[256] Parmigiani G. Utility in health studies. In: Rosner B, Glynn R, eds., Encyclopedia of Biostatistics.
New York: Wiley 1998.
[257] Parmigiani G, Berry D, Iversen Jr ES, M¨
uller P, Schildkraut J, Winer E.
Modeling risk of breast
cancer and decisions about genetic testing
. In: Gatsonis C, et al., eds., Case Studies In Bayesian
Statistics, vol. IV, 173–268. Springer 1998.
[258] Iversen Jr ES, Parmigiani G, Berry D.
Validating Bayesian prediction models: a case study in
genetic susceptibility to breast cancer
. In: Gatsonis C, Kass RE, Carlin B, Carriquiry A, Gelman
A, Verdinelli I, West M, eds., Case Studies In Bayesian Statistics, vol. IV, 321–338. NY: Springer
1998.
[259] Parmigiani G.
Decision models in screening for breast cancer
. In: Bernardo JM, Berger JO, Dawid
AP, Smith AFM, eds., Bayesian Statistics 6, 525–546. Oxford: Oxford University Press 1999.
[260] Dominici F, Parmigiani G. Combining studies with continuous and dichotomous responses: a
latent variables approach. In: Stangl DK, Berry DA, eds., Meta–analysis in Medicine and Health
Policy, vol. 151, 105–126. New York, NY, USA: Marcel Dekker 2000.
[261] Parmigiani G. Decision theory: Bayesian. In: Smelser N, Baltes P, eds., International Encyclopedia
of Social and Behavioral Sciences, 3327–3334. Oxford: Elsevier 2001.
[262] Parmigiani G, Garrett ES, Irizarry RA, Zeger SL. The analysis of gene expression data: an overview
of methods and software. In: Parmigiani G, Garrett ES, Irizarry RA, Zeger SL, eds., The analysis
of gene expression data: methods and software, 1–45. New York: Springer 2003.
[263] Garrett ES, Parmigiani G. POE: Statistical tools for molecular profiling. In: Parmigiani G, Garrett
ES, Irizarry RA, Zeger SL, eds., The analysis of gene expression data: methods and software,
362–387. New York: Springer 2003.
[264] Parmigiani G, Garrett E, Azbazhagan B, Gabrielson E. Molecular classification of lung cancer - a
cross-platform comparison of gene epxression data sets. Chest 125(5); 103S 2004.
[265] Garrett ES, Parmigiani G.
Clustering and classification methods for gene expression data analysis
.
In: Nuber U, ed., DNA Microarrays: Advanced Methods, 241–256. New York: Taylor and Francis
2005.
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[266] Shen Y, Parmigiani G. Optimization of breast cancer screening modalities. In: Nikoulina, Com-
menges, Huber, eds., Probability, Statistics and Modeling in Public Health, 405–420. New York:
Springer 2006.
[267] M¨
uller P, Parmigiani G, Rice K.
FDR and Bayesian multiple comparisons rules
. In: Bernardo JM,
Bayarri S, Berger JO, Dawid A, Heckerman D, Smith AFM, West M, eds., Bayesian Statistics 8.
Oxford University Press 2007.
[268] Parmigiani G, Blackford A. Familial cancer risk assessment using BayesMendel. In: Casagrande
J, Davuluri R, Ochs M, eds., Biomedical Informatics for Cancer Research. Springer 2010.
[269] Zhong X, Marchionni L, Cope L, Iversen ES, Garrett-Mayer ES, Gabrielson E, Parmigiani G. Op-
timized cross-study analysis of microarray-based predictors. In: Do KA, Qin S, Vannucci M, eds.,
Advances in Statistical Bioinformatics: Models and Integrative Inference for High-Throughput
Data, 398. Cambridge University Press 2013.
[270] Parmigiani G, Boca S, Ding J, Trippa L. Gene Function Analysis, Methods in Molecular Biology,
chap. Statistical Tools and R Software for Cancer Driver Probabilities, 113–134. Humana Press
2014.
[271] Tyekucheva S, Parmigiani G. Bioinformatic analysis of epidemiological and pathological data. In:
Loda M, Mucci L, Mittelstadt ML, Hemelrijck MV, Cotter MB, eds., Pathology and Epidemiology
of Cancer, 91–105. Springer 2016.
Book Reviews Comments and Responses
[272] Parmigiani G.
Review of “Scientific reasoning: The Bayesian approach”
. Journal of the American
Statistical Association 86; 825–827 1991.
[273] Parmigiani G.
Review of “Large deviation techniques in decision, simulation and estimation”
.
Technometrics 34; 120–121 1992.
[274] Parmigiani G. Comment on “Several Bayesians: A review”. Test Madrid 2; 24–25 1993.
[275] Clyde M, DeSimone H, G. P. Comment on: Accounting for model uncertainty in survival analysis
improves predictive performance, by Raftery et al. In: Bernardo JM, Berger JO, Dawid AP,
Smith AFM, eds., Bayesian Statistics 5 – Proceedings of the Fifth Valencia International Meeting,
323–349. Clarendon Press [Oxford University Press] 1996.
[276] Berry DA, Parmigiani G.
Response to: Re: probability of carrying a mutation of breast-ovarian
cancer gene BRCA1 based on family history by Schaid, dj
. J Natl Cancer Inst 89; 1634 1997.
[277] Berry D, Parmigiani G, Rubinstein W, Watson P.
Response to Nonovarian Pelvic Cancers in
BRCA1/2 Mutation Carriers and the BRCAPRO Statistical Model by Cremin et al.
J Clin Oncol
20; 3936–3937 2002.
[278] Chen S, Iversen ESJ, Parmigiani G.
In Reply to: BRCA1 and BRCA2 Cancer Risks by Antoniou
et al
. J Clin Oncol 24; 3313–3314 2006.
[279] Parmigiani G, Chen S.
In Reply to: One Risk Fits All? by De Bock et al.
J Clin Oncol 25; 3384–
2007.
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