Merlise Clyde | Scholars@Duke

Merlise Clyde
Professor of Statistical Science

Model uncertainty and choice in prediction and variable selection problems for linear, generalized linear models and multivariate models. Bayesian Model Averaging. Prior distributions for model selection and model averaging. Wavelets and adaptive kernel non-parametric function estimation. Spatial statistics. Experimental design for nonlinear models. Applications in proteomics, bioinformatics, astro-statistics, air pollution and health effects, and environmental sciences.

Office Hours

See individual course pages for office hours associated with courses.

Current Appointments & Affiliations

Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2011

Contact Information

223E Old Chem Bldg, Box 90251, Durham, NC 27708
Duke Box 90251, Durham, NC 27708-0251
clyde@duke.edu (919) 681-8440
GitHub Profile
Personal site

Background
Education, Training, & Certifications
- Ph.D., University of Minnesota, Twin Cities 1993
- M.S., University of California - Riverside 1988
- M.S., University of Alberta (Canada) 1986
- B.S., Oregon State University 1985
Duke Appointment History
- Chair in the Department of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2013 - 2019
- Associate Professor in the Institute for Statistics and Decision Sciences, Statistical Science, Trinity College of Arts & Sciences 2000 - 2011
- Assistant Professor in the Institute of Statistics and Decision Sciences, Statistical Science, Trinity College of Arts & Sciences 1993 - 2000
Leadership & Clinical Positions at Duke
- Chair Department of Statistical Science 2013-2019
Recognition
In the News
- MAY 22, 2020 Trinity College of Arts and Sciences
  
  Clyde, Reiter Named Institute of Mathematical Statistics Fellows
- DEC 9, 2013 Durham Herald-Sun
  
  Duke trustees approve six new graduate programs
Awards & Honors
Expertise
Subject Headings
Research
Selected Grants
- Quantifying and Communicating Numerical Model Uncertainty awarded by University of North Carolina - Chapel Hill 2019 - 2021
- Statistical and Applied Mathematical Science Institute awarded by University of North Carolina - Chapel Hill 2017 - 2020
- Models for Consortium Level Analysis of GxE Interaction in Complex Disease awarded by National Institutes of Health 2012 - 2015
- Advances in Bayesian Model Choice awarded by National Science Foundation 2011 - 2015
- Bayesian Modeling and Optimal Design for Studies of Gene-Environment Association awarded by National Institutes of Health 2007 - 2011
- Multimodality Word-Finding in Neurosurgical Language Mapping awarded by National Institutes of Health 2007 - 2011
- Collaborative Research: Adaptive Experimental Design for Astronomical Exploration awarded by National Science Foundation 2005 - 2010
- Large Scale Model Averaging and Model Selection awarded by National Science Foundation 2004 - 2007
- SCREMS: Distributed Environments for Stochastic Computation awarded by National Science Foundation 2004 - 2007
- Spatial-temporal Models for Environmental Health Effects awarded by Environmental Protection Agency 2001 - 2006
- Model Uncertainty, Model Selection, and Robustness with Application in Environmental Science awarded by National Science Foundation 1998 - 2004
- Model Uncertainty in Health Effect Studies of Particulate Matter awarded by Environmental Protection Agency 1999 - 2001
- Model Uncertainty In Prediction, Variable Selection and Related Decision Problems awarded by National Science Foundation 1996 - 2000
External Relationships
- Coursera
- JASP
- Project Euclid
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Li, Y., & Clyde, M. A. (2018). Mixtures of g-priors in Generalized Linear Models. Journal of the American Statistical Association, 113(524), 1828–1845. https://doi.org/10.1080/01621459.2018.1469992
    Full Text Open Access Copy Link to Item
  - Day, D. B., Clyde, M. A., Xiang, J., Li, F., Cui, X., Mo, J., … Zhang, J. J. (2018). Age modification of ozone associations with cardiovascular disease risk in adults: a potential role for soluble P-selectin and blood pressure. Journal of Thoracic Disease, 10(7), 4643–4652. https://doi.org/10.21037/jtd.2018.06.135
    Full Text
  - Day, D. B., Xiang, J., Mo, J., Clyde, M. A., Weschler, C. J., Li, F., … Zhang, J. (2018). Combined use of an electrostatic precipitator and a high-efficiency particulate air filter in building ventilation systems: Effects on cardiorespiratory health indicators in healthy adults. Indoor Air, 28(3), 360–372. https://doi.org/10.1111/ina.12447
    Full Text
  - Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E.-J., Berk, R., … Johnson, V. E. (2018). Redefine statistical significance. Nature Human Behaviour, 2(1), 6–10. https://doi.org/10.1038/s41562-017-0189-z
    Full Text Open Access Copy
  - RE: “RISK PREDICTION FOR EPITHELIAL OVARIAN CANCER IN 11 UNITED STATES–BASED CASE-CONTROL STUDIES: INCORPORATION OF EPIDEMIOLOGIC RISK FACTORS AND 17 CONFIRMED GENETIC LOCI”. (2017). American Journal of Epidemiology, 186(1), 130–130. https://doi.org/10.1093/aje/kwx151
    Full Text
  - Clyde, M. A., Palmieri Weber, R., Iversen, E. S., Poole, E. M., Doherty, J. A., Goodman, M. T., … , on behalf of the Ovarian Cancer Association Consortium, . (2016). Risk Prediction for Epithelial Ovarian Cancer in 11 United States-Based Case-Control Studies: Incorporation of Epidemiologic Risk Factors and 17 Confirmed Genetic Loci. Am J Epidemiol, 184(8), 579–589. https://doi.org/10.1093/aje/kww091
    Full Text Open Access Copy Link to Item
  - Chou, N. D., Serafini, S., Grant, G. A., Clyde, M., Komisarow, J., & Muh, C. R. (2016). 127 Multimodality Word-Finding Distinctions in Pediatric Cortical Stimulation Mapping. Neurosurgery, 63 Suppl 1, 152. https://doi.org/10.1227/01.neu.0000489697.88290.88
    Full Text Link to Item
  - Chou, N. D., Serafini, S., Grant, G. A., Clyde, M., Komisarow, J., & Muh, C. R. (2016). 127 Multimodality Word-Finding Distinctions in Pediatric Cortical Stimulation Mapping. Neurosurgery, 63(CN_suppl_1), 152. https://doi.org/10.1227/01.neu.0000489697.88290.88
    Full Text Link to Item
  - Iversen, E. S., Lipton, G., Clyde, M. A., & Monteiro, A. N. A. (2014). Functional Annotation Signatures of Disease Susceptibility Loci Improve SNP Association Analysis. Bmc Genomics, 15, 398–398. https://doi.org/10.1186/1471-2164-15-398
    Full Text Open Access Copy
  - Clyde, M. A., & Ghosh, J. (2012). Finite population estimators in stochastic search variable selection. Biometrika, 99(4), 981–988. https://doi.org/10.1093/biomet/ass040
    Full Text Open Access Copy
  - Loredo, T. J., Berger, J. O., Chernoff, D. F., Clyde, M. A., & Liu, B. (2012). Bayesian methods for analysis and adaptive scheduling of exoplanet observations. Statistical Methodology, 9(1–2), 101–114. https://doi.org/10.1016/j.stamet.2011.07.005
    Full Text
  - Ghosh, J., & Clyde, M. A. (2011). Rao-blackwellization for Bayesian variable selection and model averaging in linear and binary regression: A novel data augmentation approach. Journal of the American Statistical Association, 106(495), 1041–1052. https://doi.org/10.1198/jasa.2011.tm10518
    Full Text
  - Clyde, M. A., Ghosh, J., & Littman, M. L. (2011). Bayesian adaptive sampling for variable selection and model averaging. Journal of Computational and Graphical Statistics, 20(1), 80–101. https://doi.org/10.1198/jcgs.2010.09049
    Full Text
  - Armagan, A., Dunson, D. B., & Clyde, M. (2011). Generalized Beta Mixtures of Gaussians. Advances in Neural Information Processing Systems, 24, 523–531.
  - House, L. L., Clyde, M. A., & Wolpert, R. L. (2011). Bayesian nonparametric models for peak identification in MALDI-TOF mass spectroscopy. The Annals of Applied Statistics, 5(2B), 1488–1511. https://doi.org/10.1214/10-AOAS450
    Full Text Open Access Copy Link to Item
  - Wolpert, R. L., Clyde, M. A., & Tu, C. (2011). Stochastic expansions using continuous dictionaries: Lévy adaptive regression kernels. Annals of Statistics, 39(4), 1916–1962. https://doi.org/10.1214/11-AOS889
    Full Text Open Access Copy
  - Wilson, M. A., Iversen, E. S., Clyde, M. A., Schmidler, S. C., & Schildkraut, J. M. (2010). BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES. Ann Appl Stat, 4(3), 1342–1364. https://doi.org/10.1214/09-aoas322
    Full Text Open Access Copy Link to Item
  - Schildkraut, J. M., Iversen, E. S., Wilson, M. A., Clyde, M. A., Moorman, P. G., Palmieri, R. T., … Berchuck, A. (2010). Association between DNA damage response and repair genes and risk of invasive serous ovarian cancer. Plos One, 5(4), e10061. https://doi.org/10.1371/journal.pone.0010061
    Full Text Open Access Copy Link to Item
  - Jesneck, J. L., Mukherjee, S., Yurkovetsky, Z., Clyde, M., Marks, J. R., Lokshin, A. E., & Lo, J. Y. (2009). Do serum biomarkers really measure breast cancer? Bmc Cancer, 9, 164. https://doi.org/10.1186/1471-2407-9-164
    Full Text Link to Item
  - Schildkraut, J., Iversen, E., Marks, J., Wilson, M., Clyde, M., Palmieri, R., … Berchuck, A. (2009). Association between serous invasive ovarian cancer and variants in candidate DNA damage response genes. Cancer Research, 69.
    Link to Item
  - Schildkraut, J. M., Goode, E. L., Clyde, M. A., Iversen, E. S., Moorman, P. G., Berchuck, A., … Australian Ovarian Cancer Study Group, . (2009). Single nucleotide polymorphisms in the TP53 region and susceptibility to invasive epithelial ovarian cancer. Cancer Res, 69(6), 2349–2357. https://doi.org/10.1158/0008-5472.CAN-08-2902
    Full Text Link to Item
  - Zhou, X. K., Clyde, M. A., Garrett, J., Lourdes, V., O’Connell, M., Parmigiani, G., … Wiles, T. (2009). Statistical methods for automated drug susceptibility testing: Bayesian minimum inhibitory concentration prediction from growth curves. Annals of Applied Statistics, 3(2), 710–730. https://doi.org/10.1214/08-AOAS217
    Full Text
  - Chu, J. H., Clyde, M. A., & Liang, F. (2009). Bayesian function estimation using continuous wavelet dictionaries. Statistica Sinica, 19(4), 1419–1438.
    Link to Item
  - Palmieri, R. T., Wilson, M. A., Iversen, E. S., Clyde, M. A., Calingaert, B., Moorman, P. G., … Australian Ovarian Cancer Study Group, . (2008). Polymorphism in the IL18 gene and epithelial ovarian cancer in non-Hispanic white women. Cancer Epidemiol Biomarkers Prev, 17(12), 3567–3572. https://doi.org/10.1158/1055-9965.EPI-08-0548
    Full Text Link to Item
  - Liang, F., Paulo, R., Molina, G., Clyde, M. A., & Berger, J. O. (2008). Mixtures of g priors for Bayesian variable selection. Journal of the American Statistical Association, 103(481), 410–423. https://doi.org/10.1198/016214507000001337
    Full Text
  - Clyde, M. A., Berger, J. O., Bullard, F., Ford, E. B., Jefferys, W. H., Luo, R., … Loredo, T. (2007). Current challenges in Bayesian model choice. Statistical Challenges in Modern Astronomy Iv, 371, 224–240.
    Link to Item
  - Kuncel, A. M., Cooper, S. E., Wolgamuth, B. R., Clyde, M. A., Snyder, S. A., Montgomery, E. B., … Grill, W. M. (2006). Clinical response to varying the stimulus parameters in deep brain stimulation for essential tremor. Movement Disorders : Official Journal of the Movement Disorder Society, 21(11), 1920–1928. https://doi.org/10.1002/mds.21087
    Full Text
  - Berger, J., Dette, H., Lugosi, G., & Munk, A. (2005). Statistische und Probabilistische Methoden der Modellwahl. Oberwolfach Reports, 2611–2704. https://doi.org/10.4171/owr/2005/47
    Full Text Open Access Copy
  - House, L., Clyde, M. A., & Huang, Y. C. (2005). Bayesian Identification of Differential Gene Expression Induced by Metals in Human Bronchial Epithelial Cells. Bayesisan Analysis, 1(1), 105–120. https://doi.org/10.1214/06-BA103
    Full Text
  - Goodman, A. M., Clyde, M. A., Burdick, D. S., Idriss, S. F., & Wolf, P. D. (2004). Minimum energy single-shock internal atrial defibrillation in sheep. J Interv Card Electrophysiol, 10(2), 131–138. https://doi.org/10.1023/B:JICE.0000019266.09648.f6
    Full Text Link to Item
  - Clyde, M., & George, E. I. (2004). Model uncertainty. Statistical Science, 19(1), 81–94. https://doi.org/10.1214/088342304000000035
    Full Text
  - Lee, H. K. H., & Clyde, M. A. (2004). Lossless online Bayesian bagging. Journal of Machine Learning Research, 5, 143–151.
    Open Access Copy Link to Item
  - Clyde, M. A., & George, E. I. (2003). Invited discussion of ``Wavelet-Based Nonparametric Modeling of Hierarchical Functions in Colon Carcinogenesis'' by J.S. Morris, M. Vannucci, P.J. Brown, and R.J. Carroll. (null) Journal of the American Statistical Association, 98(463), 584–585. https://doi.org/10.1198/016214503000000440
    Full Text
  - Dominici, F., Sheppard, L., & Clyde, M. (2003). Health effects of air pollution: A statistical review. International Statistical Review, 71(2), 243–276. https://doi.org/10.1111/j.1751-5823.2003.tb00195.x
    Full Text
  - Clyde, M., & Chaloner, K. (2002). Constrained design strategies for improving normal approximations in nonlinear regression problems. Journal of Statistical Planning and Inference, 104(1), 175–196. https://doi.org/10.1016/S0378-3758(01)00239-7
    Full Text
  - Clyde, M., & Lee, H. K. (2001). Bagging and the Bayesian Bootstrap. Artificial Intelligence and Statistics, 8, 169–174.
    Open Access Copy Link to Item
  - Clyde, M. (2000). Model uncertainty and health effect studies for particulate matter. Environmetrics, 11(6), 745–763. https://doi.org/10.1002/1099-095X(200011/12)11:6<745::AID-ENV431>3.0.CO;2-N
    Full Text
  - Clyde, M., & George, E. I. (2000). Flexible empirical Bayes estimation for wavelets. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 62(4), 681–698. https://doi.org/10.1111/1467-9868.00257
    Full Text
  - Dominici, F., Parmigiani, G., & Clyde, M. (2000). Conjugate analysis of multivariate normal data with incomplete observations. Canadian Journal of Statistics, 28(3), 533–550. https://doi.org/10.2307/3315963
    Full Text
  - Lamon, E. C., & Clyde, M. A. (2000). Accounting for model uncertainty in prediction of chlorophyll a in Lake Okeechobee. Journal of Agricultural, Biological, and Environmental Statistics, 5(3), 297–322. https://doi.org/10.2307/1400456
    Full Text
  - Clyde, M. (1999). Comment. Statistical Science, 14(4), 401–404.
  - Clyde, M. A. (1999). Comment on ``Bayesian Model Averaging: A Tutorial'' by Hoeting, JA., Madigan,D., Raftery, AE., and Volinsky, CT. Statistical Science, 14, 401–404. https://doi.org/10.1214/ss/1009212519
    Full Text Open Access Copy
  - MacEachern, S. N., Clyde, M., & Liu, J. S. (1999). Sequential importance sampling for nonparametric Bayes models: The next generation. Canadian Journal of Statistics, 27(2), 251–267. https://doi.org/10.2307/3315637
    Full Text
  - Clyde, M. A., & Parmigiani, G. (1998). Protein construct storage: Bayesian variable selection and prediction with mixtures. Journal of Biopharmaceutical Statistics, 8(3), 431–443. https://doi.org/10.1080/10543409808835251
    Full Text
  - Clyde, M., Parmigiani, G., & Vidakovic, B. (1998). Multiple shrinkage and subset selection in wavelets. Biometrika, 85(2), 391–401. https://doi.org/10.1093/biomet/85.2.391
    Full Text
  - Clyde, M. A. (1997). Strategies for Model Mixing in Generalized Linear Models. Artificial Intelligence and Statistics, 6, 103–114.
  - Clyde, M. A. (1997). Strategies for Model Mixing in Generalized Linear Models. Artificial Intelligence and Statistics, 6, 103–114.
  - Clyde, M., & Chaloner, K. (1996). The equivalence of constrained and weighted designs in multiple objective design problems. Journal of the American Statistical Association, 91(435), 1236–1244. https://doi.org/10.1080/01621459.1996.10476993
    Full Text
  - Clyde, M. A., DeSimone, H., & Parmigiani, G. (1996). Prediction via orthogonalized model mixing. Journal of the American Statistical Association, 91, 1197–1208. https://doi.org/10.2307/2291738
    Full Text
  - Furnier, G. R., Stine, M., Mohn, C. A., & Clyde, M. A. (1991). Geographic patterns of variation in allozymes and height growth in white spruce. Canadian Journal of Forest Research, 21(5), 707–712. https://doi.org/10.1139/x91-097
    Full Text
  - Clyde, M. A. (1987). Radial and longitudinal variation in stem diameter increment of lodgepole pine, white spruce, and black spruce: species and crown class differences. Canadian Journal of Forest Research, 1223–1227.
  - Clyde, M. A. (1987). A new computerized system for tree ring measurement and analysis. Forestry Chronicle, 63, 23–27.
  - Furnier, G. R., Knowles, P., Clyde, M. A., & Dancik, B. P. (1987). Effects of avian seed dispersal on the genetic structure of whitebark pine populations. Evolution, 41(3), 607–612. https://doi.org/10.1111/j.1558-5646.1987.tb05831.x
    Full Text
- Book Sections
  - Clyde, M. A. (2015). Experimental Design: Bayesian Designs. In International Encyclopedia of the Social & Behavioral Sciences: Second Edition (pp. 521–526). https://doi.org/10.1016/B978-0-08-097086-8.42121-5
    Full Text
  - Clyde, M. A. (2015). Experimental Design: Bayesian Designs. In International Encyclopedia of the Social & Behavioral Sciences: Second Edition (pp. 521–526). https://doi.org/10.1016/B978-0-08-097086-8.42121-5
    Full Text
  - Serafini, S., Clyde, M. A., Husain, A. M., & Haglund, M. M. (2015). Brain Mapping and Monitoring. In A. M. Husain (Ed.), Practical Epilepsy (pp. 192–199). Demos Medical Publishing, LLC.
    Link to Item
  - Clydec, M., & Iversen, E. S. (2013). Bayesian model averaging in the M-open framework. In Bayesian Theory and Applications (pp. 483–498). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199695607.003.0024
    Full Text Open Access Copy
  - Clyde, M. A., & Wolpert, R. L. (2011). Discussion of ``Polson and Scott: Shrink globally, act locally: Sparse Bayesian regularization and prediction''. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 9 (pp. 528–529). Oxford University Press.
  - Clyde, M. A., & Wolpert, R. L. (2011). Discussion of ``Polson and Scott: Shrink globally, act locally: Sparse Bayesian regularization and prediction''. In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 9 (pp. 528–529). Oxford University Press.
  - Clyde, M. A., & Wolpert, R. L. (2007). Nonparametric Function Estimation using Overcomplete Dictionaries (with Discussion). In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 8 (pp. 91–114). Oxford University Press.
  - Clyde, M. A., & Wolpert, R. L. (2007). Nonparametric Function Estimation using Overcomplete Dictionaries (with Discussion). In J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 8 (pp. 91–114). Oxford University Press.
  - Clyde, M. A., House, L., & Wolpert, R. L. (2006). Nonparametric Models for Proteomic Peak Identification and Quantification. In K.-A. Do, P. Müller, & M. Vannucci (Eds.), Bayesian Inference for Gene Expression and Proteomics (pp. 293–308). Cambridge University Press.
  - Clyde, M. (2003). Model Averaging. In S. J. Press (Ed.), Subjective and Objective Bayesian Statistics: Principles, Models, and Applications. John Wiley & Sons.
  - Clyde, M. (2003). Invited discussion of "Bayesian and Frequentist Multiple Testing, by C. Genovese and L. Wasserman". In J. M. Bernardo, M. J. Bayarri, A. P. Dawid, J. O. Berger, D. Heckerman, A. F. M. Smith, & M. West (Eds.), Bayesian Statistics 7 (pp. 157–160). Oxford University Press.
  - Clyde, M. (2001). Discussion of Hugh Chipman, Edward I. George and Robert E. McCulloch, "The Practical Implementation of Bayesian Model Selection". In Institute of Mathematical Statistics Lecture Notes - Monograph Series (pp. 117–124). Institute of Mathematical Statistics. https://doi.org/10.1214/lnms/1215540965
    Full Text Open Access Copy
  - Clyde, M. A. (2001). Experimental Design: Bayesian Designs. In International Encyclopedia of the Social & Behavioral Sciences (pp. 5075–5081). Elsevier. https://doi.org/10.1016/b0-08-043076-7/00421-6
    Full Text
  - Clyde, M. A. (1999). Bayesian Model Averaging and Model Search Strategies (with Discussion). In J. M. Bernardo, A. P. Dawid, J. O. Berger, & A. F. M. Smith (Eds.), Bayesian Statistics 6 (Vol. 6, pp. 157–185). Oxford University Press.
    Link to Item
  - Clyde, M. A., & George, E. I. (1999). Empirical Bayes Estimation in Wavelet Nonparametric Regression. In Bayesian Inference in Wavelet-Based Models (pp. 309–322). Springer New York. https://doi.org/10.1007/978-1-4612-0567-8_19
    Full Text
  - Paddock, S., West, M., Young, S. S., & Clyde, M. (1999). Mixture Models in the Exploration of Structure-Activity Relationships in Drug Design. In Case Studies in Bayesian Statistics (pp. 339–353). Springer New York. https://doi.org/10.1007/978-1-4612-1502-8_9
    Full Text
  - Clyde, M. A., Parmigiani, G., & Vidakovic, B. (1997). Using Markov chain Monte Carlo to account for model uncertainty, with applications to wavelets. In L. Billard & N. I. Fisher (Eds.), Computing science and statistics. (Vol. 28, pp. 209–218). Fairfax Station, VA: Interface Foundation of North America,.
  - Clyde, M. A., Parmigiani, G., & Vidakovic, B. (1997). Using Markov chain Monte Carlo to account for model uncertainty, with applications to wavelets. In L. Billard & N. I. Fisher (Eds.), Computing science and statistics. (Vol. 28, pp. 209–218). Fairfax Station, VA: Interface Foundation of North America,.
  - Clyde, M. A., Muller, P., & Parmigiani, G. (1996). Inference and design strategies for a hierarchical logistic regression model. In D. A. Berry & D. K. Stangl (Eds.), Bayesian Biostatistics (Vol. 151, pp. 297–320). New York, NY: Marcel Dekker.
    Link to Item
  - Clyde, M. A., Muller, P., & Parmigiani, G. (1996). Inference and design strategies for a hierarchical logistic regression model. In D. A. Berry & D. K. Stangl (Eds.), Bayesian Biostatistics (Vol. 151, pp. 297–320). New York, NY: Marcel Dekker.
    Link to Item
  - Clyde, M., & Parmigiani, G. (1996). Orthogonalizations and Prior Distributions for Orthogonalized Model Mixing. In Modelling and Prediction Honoring Seymour Geisser (pp. 206–227). Springer New York. https://doi.org/10.1007/978-1-4612-2414-3_13
    Full Text
  - Clyde, M. A. (1995). Bayesian Designs for Approximate Normality. In C. P. Kitsos & W. G. Muller (Eds.), MODA 4 -- Advances in Model--Oriented Data Analysis (pp. 25–35). Physica-Verlag. https://doi.org/10.1007/978-3-662-12516-8
    Full Text Link to Item
  - Clyde, M., DeSimone, H., & Parmigiani, G. (1995). Discussion of "Accounting for Model Uncertainty in Survival Analysis Improves Predictive Performance by A.E. Raftery, D.M. Madigan and C.T. Volinsky". In J. O. Berger, J. M. Bernardo, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian Statistics 5 (Vol. 5, pp. 341–341). Oxford University Press.
  - Clyde, M., Müller, P., & Parmigiani, G. (1995). Optimal Design for Heart Defibrillators. In Lecture Notes in Statistics (pp. 278–292). Springer New York. https://doi.org/10.1007/978-1-4612-2546-1_7
    Full Text
  - Clyde, M., & Strauss, D. (1991). Logistic regression for spatial pair-potential models. In Institute of Mathematical Statistics Lecture Notes - Monograph Series (pp. 14–30). Institute of Mathematical Statistics. https://doi.org/10.1214/lnms/1215460490
    Full Text
  - Clyde, M., & Strauss, D. (1991). Logistic regression for spatial pair-potential models. In Institute of Mathematical Statistics Lecture Notes - Monograph Series (pp. 14–30). Institute of Mathematical Statistics. https://doi.org/10.1214/lnms/1215460490
    Full Text
  - Clyde, M. A., House, L. L., Wolpert, R. L., & Vannucci, M. (n.d.). Nonparametric Models for Proteomic Peak Identification and Quantification. In Bayesian Inference for Gene Expression and Proteomics (pp. 293–308). Cambridge University Press. https://doi.org/10.1017/cbo9780511584589.016
    Full Text
- Conference Papers
  - Ness, R., Clyde, M., Palmieri, R., & Schildkraut, J. (2017). Risk prediction for ovarian cancer: epidemiologic risk factors plus confirmed genetic loci. In Bjog an International Journal of Obstetrics and Gynaecology (Vol. 124, pp. 159–159). WILEY.
    Link to Item
  - Clyde, M. A., Weber, R. P., Ness, R., & Schildkraut, J. (2016). RISK PREDICTION FOR OVARIAN CANCER: EPIDEMIOLOGIC RISK FACTORS PLUS CONFIRMED GENETIC LOCI. In International Journal of Gynecological Cancer (Vol. 26, pp. 28–28). LIPPINCOTT WILLIAMS & WILKINS.
    Link to Item
  - Clyde, M. A., DeSimone, H., & Parmigiani, G. (1994). A Comparison of Algorithms for Sampling Models. In Proceedings of the 1994 Joint Statistical Meetings; Section on Bayesian Statistical Science (pp. 211–216).
    Link to Item
- Software
  - Clyde, M. A. (2016). BAS: Bayesian Model Averaging using Bayesian Adaptive Sampling. CRAN. https://doi.org/10.5281/zenodo.59497
    Full Text Link to Item
Teaching & Mentoring
Recent Courses
- STA 493: Research Independent Study 2021
- MATH 743L: Linear Models 2020
- STA 493: Research Independent Study 2020
- STA 701S: Readings in Statistical Science 2020
- STA 721L: Linear Models 2020
- STA 790-1: Special Topics in Statistics 2020
- MATH 743: Linear Models 2019
- STA 521L: Predictive Modeling and Statistical Learning 2019
- STA 721: Linear Models 2019
Scholarly, Clinical, & Service Activities
Presentations & Appearances
- Model Uncertainty and Uncertainty Quantification. SIAM Uncertainty Quantification UQ18. SIAM. April 2018 2018
Service to the Profession
Service to Duke
- Duke University. Provost Committee on Tenure Standards. 2017 - 2018 2017 - 2018
- Faculty Compensation Committee. 2012 - 2018 2012 - 2018
- Duke University. Executive Committee of the Graduate Faculty. 2008 - 2012 2008 - 2012

Some information on this profile has been compiled automatically from Duke databases and external sources. (Our About page explains how this works.) If you see a problem with the information, please write to Scholars@Duke and let us know. We will reply promptly.

Education, Training, & Certifications

Duke Appointment History

Leadership & Clinical Positions at Duke

In the News

Awards & Honors

Subject Headings

Selected Grants

External Relationships

Selected Publications

Academic Articles

Book Sections

Conference Papers

Software

Recent Courses

Presentations & Appearances

Service to the Profession

Service to Duke