Research Interests
Statistical Causality, Treatment Heterogeneity, High-dimensional data analysis, Applications of statistics in medicine, biology, chemistry, and the environment.
Publications
Peer reviewed and book chapters, in print or in press
Kaiser, K.A., Gadbury G.L. Estimating the Range of Obesity Treatment Response Variability in Humans: Methods and Illustrations. Human Heredity 75, 127 – 135.
Lianqing Zheng, Gary L. Gadbury, Jyoti Shah, and Ruth Welti (2013). Exploration of reactantproduct lipid pairs in mutant-wild type lipidomics experiments. Proceedings of the 2012 Conference on Applied Statistics in Agriculture, Kansas State University, Manhattan, KS.
Troy E. Richardson, Gary L. Gadbury (2013). Treatment heterogeneity and potential outcomes in linear mixed effects models. Proceedings of the 2012 Conference on Applied Statistics in Agriculture, Kansas State University, Manhattan, KS.
Edwin A. Ndum, Jeffrey M. Albert, Gary L. Gadbury (2012). Individual treatment heterogeneity in a three period two treatment cross-over design. JP Journal of Biostatistics. 8, 1 - 35.
Gary L. Gadbury and David B. Allison (2012). Inappropriate fiddling with statistical analyses to obtain a desirable p-value: Tests to detect its presence in published literature. PLoS ONE, 7(10): e46363.
Loop, M.S., Wood, A.C., Thomas, A.S., Dhurandhar, E.J., Shikany, J.M., Gadbury, G.L., and Allison, D.B. Submitted for Your Consideration: Potential Advantages of a Novel Clinical Trial Design and Initial Patient Reaction. Frontiers in Genetics: Pharmacogenetics and Pharmacogenomics, 3:145. doi:10.3389/fgene.2012.00145.
Robert S. Poulson, Gary L. Gadbury, David B. Allison (2012). Treatment heterogeneity and individual qualitative interaction. American Statistician, 66, 16 - 24..
Robert Makowsky, T. Mark Beasley, Gary L. Gadbury, Jeffrey M. Albert, Richard Kennedy, David B. Allison (2011). The validity and power of extreme sampling schemes for mediation analysis. Frontiers in Genetics: Behavioral and Psychiatric Genetics, 2:75.
Xuxia Wu, Amit Patki, Cristina Lara-Castro, Xiangqin Cui, Kui Zhang, R. Grace Walton, Michael V Osier, Gary L. Gadbury, David B. Allison, Mitchell Martin, and W. Timothy Garvey (2011). Genes and Biochemical Pathways in Human Skeletal Muscle Affecting Resting Energy Expenditure and Fuel Partitioning. Journal of Applied Physiology. 110: 746 – 755.
Jumpponen A., Keating K., Gadbury G., Jones KL., Mattox JD (2010). Multi-element fingerprinting in high throughput sequencing identify multiple elements that affect fungal communities in Quercus macrocarpa foliage. Plant Signaling & Behavior. 5, 1157 - 1161.
Gadbury G. L. (2010). Subject – Treatment Interaction. In Encyclopedia of Biopharmaceutical Statistics, Third Edition, Revised and Expanded. Edited by Shein-Chung Chow. Informa Healthcare, London. p. 1316 – 1321. (updated print entry from 2004 online entry to 2nd ed.)
Xiaojun Hu, Gary L. Gadbury, Qinfang Xiang, David B. Allison (2010). Illustrations on using the distribution of a p-value in high dimensional data analysis. Advances and Applications in Statistical Science. 1, 191 – 213.
Gadbury GL, Garrett KG, Allison DB (2009). Challenges and Approaches to Statistical Design and Inference in High Dimensional Investigations. Plant Systems Biology, Series in Methods in Molecular Biology, Belostotsky D (ed). Totowa, NJ: Humana Press Inc. 181 – 206.
Gary L. Gadbury, *Qinfang Xiang, Lin Yang, Stephen Barnes, Grier P. Page, David B. Allison (2008). Evaluating statistical methods using plasmode data sets in the age of massive public databases: An illustration using false discovery rates. Plos Genetics. 4(6): e1000098.
Gary L. Gadbury, Thidaporn Supapakorn, Christopher S. Coffey, Scott W. Keith, David B. Allison (2008). Application of potential outcomes to an intentional weight loss latent variable problem. Statistics and Its Interface, 1, 87 – 98.
Loretta D. Hunter, Gary L. Gadbury, Yue-wern Huang (2008). Atrazine exposure and breast cancer incidence: An ecological study of Missouri counties. Toxicological & Environmental Chemistry. 90, 367 – 376.
Qinfang Xiang, Jode Edwards, and Gary L. Gadbury (2006). Interval estimation in a finite mixture model: Modeling P-values in multiple testing applications. Computational Statistics and Data Analysis. 51, 570 – 586.
Mehta, T.S., Zakharkin, S.O., Gadbury, G.L., and Allison, D.B. (2006), Epistemological Issues in Omics and High-Dimensional Biology: Give the People What They Want, Physiological Genomics. 28, 24 – 32.
Stephen Barnes, David B. Allison, Grier P. Page, Mark Carpenter, Gary L. Gadbury, Sreelatha Meleth, Pamela Horn-Ross, Helen Kim, Coral A. Lamartinere (2006). Genistein and polyphenols in the study of cancer prevention: Chemistry, biology, statistics, and experimental design. In Nutritional Genomics, Discovering the Path to Personalized Nutrition. Edited by J. Kaput and R.L. Rodriguez. John Wiley & Sons, Inc., Hoboken, New Jersey. (print copy available upon request)
Grier P Page, Jode W Edwards, Gary L Gadbury, Prashanth Yelisetti, Jelai Wang, Prinal Trivedi, David B Allison (2006). The PowerAtlas: a power and sample size atlas for microarray experimental design and research. BMC Bioinformatics, 7:84.
Jeffrey M. Albert, Gary L. Gadbury, and Edward J. Mascha (2005). Assessing Treatment Effect Heterogeneity in Clinical Trials with Blocked Binary Outcomes. Biometrical Journal, 47, 662 – 673.
Gary L. Gadbury, Qinfang Xiang, Jode Edwards, Grier P. Page, and David B. Allison (2005). The role of sample size on measures of uncertainty and power. In DNA Microarrays and Related Genomics Techniques. Edited by Allison, Page, Beasley, Edwards. Taylor & Francis Group, Boca Raton.
Prinal Trivedi, Jode W. Edwards, Jelai Wang, Gary L. Gadbury, Vinodh Srinivasasainagendra, Stanislav O. Zakharkin, Kyoungmi Kim, Tapan Mehta, Jacob P. L. Brand, Amit Patki, Grier P. Page and David B. Allison (2005). HDBStat!: A platform-independent software suite for statistical analysis of high dimensional biology data. BMC Bioinformatics, 6:86.
Jode W. Edwards, Grier P. Page , Gary Gadbury, Moonseong Heo , Tsuyoshi Kayo, Richard Weindruch, David B. Allison (2005). Empirical Bayes Estimation of Gene-Specific Effects In Microarray Research. Functional & Integrative Genomics, 5, 32 – 39.
Christopher S. Coffey, Gary L. Gadbury, Kevin R. Fontaine, Chenxi Wang, Richard Weindruch, David B. Allison (2005). The effects of weight loss as a latent variable problem. Statistics in Medicine, 24, 941 – 954.
Gadbury, G. L., Iyer, H. K., and J.M. Albert (2004). Individual treatment effects in randomized trials with binary outcomes. Journal of Statistical Planning and Inference. 121, 163 – 174.
Beasley TM, Page GP, Brand JPL, Gadbury GL, Mountz JD, Allison DB (2004). Chebyshev’s inequality for non-parametric testing with small N and α in microarray research. Journal of the Royal Statistical Society, Series C (Applied Statistics). 53, 95 – 108.
Gadbury G. L. (2004). Subject – Treatment Interaction. In Encyclopedia of Biopharmaceutical Statistics, Second Edition, Revised and Expanded. Edited by Shein-Chung Chow. Marcel Dekker, Inc., New York. on-line published 03/09/2004. 1 – 7. invited paper
Gary L. Gadbury, Grier P. Page, Jode Edwards, Tsuyoshi Kayo, Tomas A. Prolla, Richard Weindruch, Paska A. Permana, John Mountz, David B. Allison (2004). Power and Sample Size Estimation in High Dimensional Biology. Statistical Methods in Medical Research. 13, 325 – 338.
Fontaine K.R., Yang D, Gadbury G.L., Heshka S., Schwartz L.G., Murugesan R., Kraker J.L., Heo M., Heymsfield S.B., Allison D.B. (2003) Results of soy-based meal replacement formula on weight, anthropometry, serum lipids & blood pressure during a 40-week clinical weight loss trial. Nutrition Journal. 2:14.
Gadbury G. L., Coffey, C. S., Allison, D. B. (2003) Modern statistical methods for handling missing repeated measurements in obesity trial data: beyond LOCF. Obesity Reviews. 4, 175 – 184. (invited paper).
Gadbury, G.L., Page, G.P., Heo, M., Mountz, J.D., Allison, D.B. (2003) Randomization tests for small samples: an application for genetic expression data. Journal of the Royal Statistical Society, Series C (Applied Statistics). 52, 365 – 376.
Gadbury, G. L., and H. T. Schreuder (2003). Cause-effect relationships in analytical surveys: An illustration of statistical issues. Environmental Monitoring and Assessment, 83, 205 – 227.
Allison, D.B., Gadbury, G.L., Schwartz, L.G., Murugesan, R., Kraker, J., Heshka, S., Fontaine, K.R., and Heymsfield, S.B. (2003) A novel soy-based meal replacement formula for weight loss among obese individuals: a randomized controlled clinical trial. European Journal of Clinical Nutrition. 57, 514 – 522.
Gadbury, G. L. and H. K. Iyer. On estimating subject-treatment interaction. In Advances on Methodological and Applied Aspects of Probability and Statistics, Edited by N. Balakrishnan, Taylor & Francis, New York (2002). pp 349 – 364. (print copy available upon request)
Gadbury, G. L., Iyer, H. K., and H. T. Schreuder (2002). An adaptive analysis of covariance using tree-structured regression. Journal of Agricultural, Biological, and Environmental Statistics, 7, 42 – 57.
Allison, D. B., Gadbury, G. L., Heo, M., Fernandez, J.R., Lee, CK., Prolla, T.A., Weindruch, R. (2002). A mixture model approach for the analysis of microarray gene expression data. Computational Statistics and Data Analysis, 39, 1 – 20.
Fontaine, K. R., Gadbury, G., Heymsfield, S. B., Kral, J., Albu, J., and Allison, D. B. (2002). Quantitative prediction of body diameter in severely obese individuals. Ergonomics. 45, 49-60.
Gadbury, G. L. Iyer, H. K., and D. B. Allison (2001). Evaluating subject-treatment interaction when comparing two treatments. Journal of Biopharmaceutical Statistics. 11(4), 313 – 333.
Gadbury, G. L. (2001). Randomization inference and bias of standard errors. The American Statistician. 55, 310-313.
Gadbury, G. L. and H. K. Iyer (2000). Unit-treatment interaction and its practical consequences. Biometrics. 56, 882 – 885.
Presentations published as abstracts
Wu XX, Patki A, Lara-Castro C, Osier MV, Gadbury GL, Allison DB, Martin M, Garvey WT. Genes and Biochemical Pathways in Human Skeletal Muscle Affecting Resting Energy Expenditure and Fuel Partitioning, DIABETES Volume: 58 Pages: A362-A362 Supplement: Suppl. 1 JUN 2009.
Whitefield PD, Rutter AP, Hagen DE, Gadbury GL, Schmid O, Brinkman M, Ross, MN. In-Situ stratospheric observations of a volatile component in rocket exhaust aerosol particles. Eos Trans. AGU, 84(46). Fall Meet. Suppl., Abstract A32B-0154, 2003.
Coffey C, Gadbury G, Fontaine K, Wang CX, Weindruch R, Allison D. The effects of intentional weight loss as a latent variable problem. Obesity Research 11: A147 – A 147 Suppl. S Sept. 2003.
Albert JM, Gadbury GL. Treatment effect heterogeneity in blocked randomized trials with binary outcomes. Controlled Clinical Trials 24: 28 Suppl. 3 June 2003.
Allison, D. B., Gadbury, G., Schwartz, L. G., Murugesan, R., Kraker, J. L., Heshka, H., Heymsfield, S. B., & Heo, M. A Randomized Controlled Clinical Trial Of A Novel Meal Replacement Formula For Weight Loss Among Obese Individuals. Presentation at EXPERIMENTAL BIOLOGY 2001. March 31-April 4, 2001, Orlando, Florida. Abstract LB318.
Fernandez, J.R., Gadbury, G, Heo, M., Lee, C.K. Prolla, T. A., Weindruch, R., & Allison, D.B. (2000). Use of microarrays to detect genes differentially expressed with caloric and non-caloric restriction feeding: a focus on analytical approaches. Obesity Research Vol (1), Supp 1. p. 32S.
Other publications (non-refereed)
Loop, M.S., Wood, A.C., Thomas, A.S., Dhurandhar, E.J., Shikany, J.M., Gadbury, G.L., and Allison, D.B. (2011). Submitted for Your Consideration: Potential Advantages of a Novel Clinical Trial Design and Initial Patient Reaction. In JSM Proceedings, Alexandria, VA: American Statistical Association, 2699-2705.
Paranagama, D. and Gadbury GL. (2011) Correlation and Variance Stabilization in Large-Scale Experiments Comparing Two Group. In JSM Proceedings, Alexandria, VA: American Statistical Association, 1420-1434.
L. Gan, GL. Gadbury, PD. Whitefield, DE. Hagen, P. Lobo (2009). Modeling particulate matter emissions at the Hartsfield-Jackson Atlanta Airport. 2008 Proceedings of the American Statistical Association, Statistics and the Environment Section [CD - ROM], Alexandria, VA: American Statistical Association.
Edwin A. Ndum, Gary L. Gadbury (2009). The influence of time on individual effect variability in a two treatment, three period crossover design. 2008 Proceedings of the American Statistical Association, Biopharmaceutical Section [CD - ROM], Alexandria, VA: American Statistical Association.
Wanrong Yin, Gary L. Gadbury, V. A. Samaranayake (2005). Power and Type I Error in a Global Test of Differential Genetic Expression. Proceedings of the American Statistical Association, Biometrics Section [CD - ROM], Alexandria, VA: American Statistical Association.
Xiaojun Hu, Gary L. Gadbury, *Qinfang Xiang (2005). Distributional aspects of P-values and their uses in multiple testing applications. Proceedings of the American Statistical Association, Biometrics Section [CD - ROM], Alexandria, VA: American Statistical Association
Gary L. Gadbury, Michael S. Williams, Hans T. Schreuder (2004). Revisiting the Southern Pine Growth Decline: Where are we 10 years later. USDA Forest Service Rocky Mountain Station Research paper RMRS-GTR-124.
Gadbury GL, Rutter AP, Ye Y, Hagen DE, Whitefield PD. (2003). A study evaluating aerosol particulate concentration. Proceedings of the American Statistical Association, Section on Statistical Consulting [CD - ROM], Alexandria, VA: American Statistical Association.
Sarah Klein, Gary L. Gadbury (2003). Counter-Intuitive Probability in Risk Assessment. Proceedings of the American Statistical Association, Section on Social Statistics [CD - ROM], Alexandria, VA: American Statistical Association.
Gadbury, G. L. (2001) Book Review: “Analysis of Incomplete Multivariate Data”, by Joe Schafer. Journal of the American Statistical Association. 95: p. 1013.
Gadbury, G. L., Iyer, H. K., Schreuder, H. T., and C. Y. Ueng (1998). “A nonparametric analysis of plot basal area growth in Southeastern United States”. USDA Forest Service Rocky Mountain Station Research paper RMRS-RP-2.
C. Y. Ueng, G. L. Gadbury, and H. T. Schreuder (1997). “Robust regression analysis of growth in basal area of natural pine stands in Georgia and Alabama”. USDA Forest Service Rocky Mountain Station Research paper RM-RP-331.
Gadbury, G. L., and H. K. Iyer (1997). “Causal inference and the problem of estimating a subject by treatment interaction”. Technical Report 97/17, Department of Statistics, Colorado State University.
Gadbury, G. L., and H. K. Iyer (1997). “Issues concerning estimation of the variance of treatment effects under the Rubin model for causal inference”. Proceedings of The Biometrics Section of the Joint Statistical Meetings. American Statistical Association, Alexandria, VA.
Kaiser, K.A., Gadbury G.L. Estimating the Range of Obesity Treatment Response Variability in Humans: Methods and Illustrations. Human Heredity 75, 127 – 135.
Lianqing Zheng, Gary L. Gadbury, Jyoti Shah, and Ruth Welti (2013). Exploration of reactantproduct lipid pairs in mutant-wild type lipidomics experiments. Proceedings of the 2012 Conference on Applied Statistics in Agriculture, Kansas State University, Manhattan, KS.
Troy E. Richardson, Gary L. Gadbury (2013). Treatment heterogeneity and potential outcomes in linear mixed effects models. Proceedings of the 2012 Conference on Applied Statistics in Agriculture, Kansas State University, Manhattan, KS.
Edwin A. Ndum, Jeffrey M. Albert, Gary L. Gadbury (2012). Individual treatment heterogeneity in a three period two treatment cross-over design. JP Journal of Biostatistics. 8, 1 - 35.
Gary L. Gadbury and David B. Allison (2012). Inappropriate fiddling with statistical analyses to obtain a desirable p-value: Tests to detect its presence in published literature. PLoS ONE, 7(10): e46363.
Loop, M.S., Wood, A.C., Thomas, A.S., Dhurandhar, E.J., Shikany, J.M., Gadbury, G.L., and Allison, D.B. Submitted for Your Consideration: Potential Advantages of a Novel Clinical Trial Design and Initial Patient Reaction. Frontiers in Genetics: Pharmacogenetics and Pharmacogenomics, 3:145. doi:10.3389/fgene.2012.00145.
Robert S. Poulson, Gary L. Gadbury, David B. Allison (2012). Treatment heterogeneity and individual qualitative interaction. American Statistician, 66, 16 - 24..
Robert Makowsky, T. Mark Beasley, Gary L. Gadbury, Jeffrey M. Albert, Richard Kennedy, David B. Allison (2011). The validity and power of extreme sampling schemes for mediation analysis. Frontiers in Genetics: Behavioral and Psychiatric Genetics, 2:75.
Xuxia Wu, Amit Patki, Cristina Lara-Castro, Xiangqin Cui, Kui Zhang, R. Grace Walton, Michael V Osier, Gary L. Gadbury, David B. Allison, Mitchell Martin, and W. Timothy Garvey (2011). Genes and Biochemical Pathways in Human Skeletal Muscle Affecting Resting Energy Expenditure and Fuel Partitioning. Journal of Applied Physiology. 110: 746 – 755.
Jumpponen A., Keating K., Gadbury G., Jones KL., Mattox JD (2010). Multi-element fingerprinting in high throughput sequencing identify multiple elements that affect fungal communities in Quercus macrocarpa foliage. Plant Signaling & Behavior. 5, 1157 - 1161.
Gadbury G. L. (2010). Subject – Treatment Interaction. In Encyclopedia of Biopharmaceutical Statistics, Third Edition, Revised and Expanded. Edited by Shein-Chung Chow. Informa Healthcare, London. p. 1316 – 1321. (updated print entry from 2004 online entry to 2nd ed.)
Xiaojun Hu, Gary L. Gadbury, Qinfang Xiang, David B. Allison (2010). Illustrations on using the distribution of a p-value in high dimensional data analysis. Advances and Applications in Statistical Science. 1, 191 – 213.
Gadbury GL, Garrett KG, Allison DB (2009). Challenges and Approaches to Statistical Design and Inference in High Dimensional Investigations. Plant Systems Biology, Series in Methods in Molecular Biology, Belostotsky D (ed). Totowa, NJ: Humana Press Inc. 181 – 206.
Gary L. Gadbury, *Qinfang Xiang, Lin Yang, Stephen Barnes, Grier P. Page, David B. Allison (2008). Evaluating statistical methods using plasmode data sets in the age of massive public databases: An illustration using false discovery rates. Plos Genetics. 4(6): e1000098.
Gary L. Gadbury, Thidaporn Supapakorn, Christopher S. Coffey, Scott W. Keith, David B. Allison (2008). Application of potential outcomes to an intentional weight loss latent variable problem. Statistics and Its Interface, 1, 87 – 98.
Loretta D. Hunter, Gary L. Gadbury, Yue-wern Huang (2008). Atrazine exposure and breast cancer incidence: An ecological study of Missouri counties. Toxicological & Environmental Chemistry. 90, 367 – 376.
Qinfang Xiang, Jode Edwards, and Gary L. Gadbury (2006). Interval estimation in a finite mixture model: Modeling P-values in multiple testing applications. Computational Statistics and Data Analysis. 51, 570 – 586.
Mehta, T.S., Zakharkin, S.O., Gadbury, G.L., and Allison, D.B. (2006), Epistemological Issues in Omics and High-Dimensional Biology: Give the People What They Want, Physiological Genomics. 28, 24 – 32.
Stephen Barnes, David B. Allison, Grier P. Page, Mark Carpenter, Gary L. Gadbury, Sreelatha Meleth, Pamela Horn-Ross, Helen Kim, Coral A. Lamartinere (2006). Genistein and polyphenols in the study of cancer prevention: Chemistry, biology, statistics, and experimental design. In Nutritional Genomics, Discovering the Path to Personalized Nutrition. Edited by J. Kaput and R.L. Rodriguez. John Wiley & Sons, Inc., Hoboken, New Jersey. (print copy available upon request)
Grier P Page, Jode W Edwards, Gary L Gadbury, Prashanth Yelisetti, Jelai Wang, Prinal Trivedi, David B Allison (2006). The PowerAtlas: a power and sample size atlas for microarray experimental design and research. BMC Bioinformatics, 7:84.
Jeffrey M. Albert, Gary L. Gadbury, and Edward J. Mascha (2005). Assessing Treatment Effect Heterogeneity in Clinical Trials with Blocked Binary Outcomes. Biometrical Journal, 47, 662 – 673.
Gary L. Gadbury, Qinfang Xiang, Jode Edwards, Grier P. Page, and David B. Allison (2005). The role of sample size on measures of uncertainty and power. In DNA Microarrays and Related Genomics Techniques. Edited by Allison, Page, Beasley, Edwards. Taylor & Francis Group, Boca Raton.
Prinal Trivedi, Jode W. Edwards, Jelai Wang, Gary L. Gadbury, Vinodh Srinivasasainagendra, Stanislav O. Zakharkin, Kyoungmi Kim, Tapan Mehta, Jacob P. L. Brand, Amit Patki, Grier P. Page and David B. Allison (2005). HDBStat!: A platform-independent software suite for statistical analysis of high dimensional biology data. BMC Bioinformatics, 6:86.
Jode W. Edwards, Grier P. Page , Gary Gadbury, Moonseong Heo , Tsuyoshi Kayo, Richard Weindruch, David B. Allison (2005). Empirical Bayes Estimation of Gene-Specific Effects In Microarray Research. Functional & Integrative Genomics, 5, 32 – 39.
Christopher S. Coffey, Gary L. Gadbury, Kevin R. Fontaine, Chenxi Wang, Richard Weindruch, David B. Allison (2005). The effects of weight loss as a latent variable problem. Statistics in Medicine, 24, 941 – 954.
Gadbury, G. L., Iyer, H. K., and J.M. Albert (2004). Individual treatment effects in randomized trials with binary outcomes. Journal of Statistical Planning and Inference. 121, 163 – 174.
Beasley TM, Page GP, Brand JPL, Gadbury GL, Mountz JD, Allison DB (2004). Chebyshev’s inequality for non-parametric testing with small N and α in microarray research. Journal of the Royal Statistical Society, Series C (Applied Statistics). 53, 95 – 108.
Gadbury G. L. (2004). Subject – Treatment Interaction. In Encyclopedia of Biopharmaceutical Statistics, Second Edition, Revised and Expanded. Edited by Shein-Chung Chow. Marcel Dekker, Inc., New York. on-line published 03/09/2004. 1 – 7. invited paper
Gary L. Gadbury, Grier P. Page, Jode Edwards, Tsuyoshi Kayo, Tomas A. Prolla, Richard Weindruch, Paska A. Permana, John Mountz, David B. Allison (2004). Power and Sample Size Estimation in High Dimensional Biology. Statistical Methods in Medical Research. 13, 325 – 338.
Fontaine K.R., Yang D, Gadbury G.L., Heshka S., Schwartz L.G., Murugesan R., Kraker J.L., Heo M., Heymsfield S.B., Allison D.B. (2003) Results of soy-based meal replacement formula on weight, anthropometry, serum lipids & blood pressure during a 40-week clinical weight loss trial. Nutrition Journal. 2:14.
Gadbury G. L., Coffey, C. S., Allison, D. B. (2003) Modern statistical methods for handling missing repeated measurements in obesity trial data: beyond LOCF. Obesity Reviews. 4, 175 – 184. (invited paper).
Gadbury, G.L., Page, G.P., Heo, M., Mountz, J.D., Allison, D.B. (2003) Randomization tests for small samples: an application for genetic expression data. Journal of the Royal Statistical Society, Series C (Applied Statistics). 52, 365 – 376.
Gadbury, G. L., and H. T. Schreuder (2003). Cause-effect relationships in analytical surveys: An illustration of statistical issues. Environmental Monitoring and Assessment, 83, 205 – 227.
Allison, D.B., Gadbury, G.L., Schwartz, L.G., Murugesan, R., Kraker, J., Heshka, S., Fontaine, K.R., and Heymsfield, S.B. (2003) A novel soy-based meal replacement formula for weight loss among obese individuals: a randomized controlled clinical trial. European Journal of Clinical Nutrition. 57, 514 – 522.
Gadbury, G. L. and H. K. Iyer. On estimating subject-treatment interaction. In Advances on Methodological and Applied Aspects of Probability and Statistics, Edited by N. Balakrishnan, Taylor & Francis, New York (2002). pp 349 – 364. (print copy available upon request)
Gadbury, G. L., Iyer, H. K., and H. T. Schreuder (2002). An adaptive analysis of covariance using tree-structured regression. Journal of Agricultural, Biological, and Environmental Statistics, 7, 42 – 57.
Allison, D. B., Gadbury, G. L., Heo, M., Fernandez, J.R., Lee, CK., Prolla, T.A., Weindruch, R. (2002). A mixture model approach for the analysis of microarray gene expression data. Computational Statistics and Data Analysis, 39, 1 – 20.
Fontaine, K. R., Gadbury, G., Heymsfield, S. B., Kral, J., Albu, J., and Allison, D. B. (2002). Quantitative prediction of body diameter in severely obese individuals. Ergonomics. 45, 49-60.
Gadbury, G. L. Iyer, H. K., and D. B. Allison (2001). Evaluating subject-treatment interaction when comparing two treatments. Journal of Biopharmaceutical Statistics. 11(4), 313 – 333.
Gadbury, G. L. (2001). Randomization inference and bias of standard errors. The American Statistician. 55, 310-313.
Gadbury, G. L. and H. K. Iyer (2000). Unit-treatment interaction and its practical consequences. Biometrics. 56, 882 – 885.
Presentations published as abstracts
Wu XX, Patki A, Lara-Castro C, Osier MV, Gadbury GL, Allison DB, Martin M, Garvey WT. Genes and Biochemical Pathways in Human Skeletal Muscle Affecting Resting Energy Expenditure and Fuel Partitioning, DIABETES Volume: 58 Pages: A362-A362 Supplement: Suppl. 1 JUN 2009.
Whitefield PD, Rutter AP, Hagen DE, Gadbury GL, Schmid O, Brinkman M, Ross, MN. In-Situ stratospheric observations of a volatile component in rocket exhaust aerosol particles. Eos Trans. AGU, 84(46). Fall Meet. Suppl., Abstract A32B-0154, 2003.
Coffey C, Gadbury G, Fontaine K, Wang CX, Weindruch R, Allison D. The effects of intentional weight loss as a latent variable problem. Obesity Research 11: A147 – A 147 Suppl. S Sept. 2003.
Albert JM, Gadbury GL. Treatment effect heterogeneity in blocked randomized trials with binary outcomes. Controlled Clinical Trials 24: 28 Suppl. 3 June 2003.
Allison, D. B., Gadbury, G., Schwartz, L. G., Murugesan, R., Kraker, J. L., Heshka, H., Heymsfield, S. B., & Heo, M. A Randomized Controlled Clinical Trial Of A Novel Meal Replacement Formula For Weight Loss Among Obese Individuals. Presentation at EXPERIMENTAL BIOLOGY 2001. March 31-April 4, 2001, Orlando, Florida. Abstract LB318.
Fernandez, J.R., Gadbury, G, Heo, M., Lee, C.K. Prolla, T. A., Weindruch, R., & Allison, D.B. (2000). Use of microarrays to detect genes differentially expressed with caloric and non-caloric restriction feeding: a focus on analytical approaches. Obesity Research Vol (1), Supp 1. p. 32S.
Other publications (non-refereed)
Loop, M.S., Wood, A.C., Thomas, A.S., Dhurandhar, E.J., Shikany, J.M., Gadbury, G.L., and Allison, D.B. (2011). Submitted for Your Consideration: Potential Advantages of a Novel Clinical Trial Design and Initial Patient Reaction. In JSM Proceedings, Alexandria, VA: American Statistical Association, 2699-2705.
Paranagama, D. and Gadbury GL. (2011) Correlation and Variance Stabilization in Large-Scale Experiments Comparing Two Group. In JSM Proceedings, Alexandria, VA: American Statistical Association, 1420-1434.
L. Gan, GL. Gadbury, PD. Whitefield, DE. Hagen, P. Lobo (2009). Modeling particulate matter emissions at the Hartsfield-Jackson Atlanta Airport. 2008 Proceedings of the American Statistical Association, Statistics and the Environment Section [CD - ROM], Alexandria, VA: American Statistical Association.
Edwin A. Ndum, Gary L. Gadbury (2009). The influence of time on individual effect variability in a two treatment, three period crossover design. 2008 Proceedings of the American Statistical Association, Biopharmaceutical Section [CD - ROM], Alexandria, VA: American Statistical Association.
Wanrong Yin, Gary L. Gadbury, V. A. Samaranayake (2005). Power and Type I Error in a Global Test of Differential Genetic Expression. Proceedings of the American Statistical Association, Biometrics Section [CD - ROM], Alexandria, VA: American Statistical Association.
Xiaojun Hu, Gary L. Gadbury, *Qinfang Xiang (2005). Distributional aspects of P-values and their uses in multiple testing applications. Proceedings of the American Statistical Association, Biometrics Section [CD - ROM], Alexandria, VA: American Statistical Association
Gary L. Gadbury, Michael S. Williams, Hans T. Schreuder (2004). Revisiting the Southern Pine Growth Decline: Where are we 10 years later. USDA Forest Service Rocky Mountain Station Research paper RMRS-GTR-124.
Gadbury GL, Rutter AP, Ye Y, Hagen DE, Whitefield PD. (2003). A study evaluating aerosol particulate concentration. Proceedings of the American Statistical Association, Section on Statistical Consulting [CD - ROM], Alexandria, VA: American Statistical Association.
Sarah Klein, Gary L. Gadbury (2003). Counter-Intuitive Probability in Risk Assessment. Proceedings of the American Statistical Association, Section on Social Statistics [CD - ROM], Alexandria, VA: American Statistical Association.
Gadbury, G. L. (2001) Book Review: “Analysis of Incomplete Multivariate Data”, by Joe Schafer. Journal of the American Statistical Association. 95: p. 1013.
Gadbury, G. L., Iyer, H. K., Schreuder, H. T., and C. Y. Ueng (1998). “A nonparametric analysis of plot basal area growth in Southeastern United States”. USDA Forest Service Rocky Mountain Station Research paper RMRS-RP-2.
C. Y. Ueng, G. L. Gadbury, and H. T. Schreuder (1997). “Robust regression analysis of growth in basal area of natural pine stands in Georgia and Alabama”. USDA Forest Service Rocky Mountain Station Research paper RM-RP-331.
Gadbury, G. L., and H. K. Iyer (1997). “Causal inference and the problem of estimating a subject by treatment interaction”. Technical Report 97/17, Department of Statistics, Colorado State University.
Gadbury, G. L., and H. K. Iyer (1997). “Issues concerning estimation of the variance of treatment effects under the Rubin model for causal inference”. Proceedings of The Biometrics Section of the Joint Statistical Meetings. American Statistical Association, Alexandria, VA.
Presentations
Professional Talks
Gary Gadbury, Invited. Interdisciplinary statistical research topics and their relevance to the state and society. Presentation to the Dean’s Advisory Council, October 2012, Manhattan, KS.
Invited. Conditional network testing in high-dimensional dependent data. Interface 2012: The Future of Statistical Computing. Houston, May 16 – 18, 2012 (with Dilan Paranagama).
Gary L. Gadbury, Robert Poulson, David Allison. Treatment heterogeneity and individual qualitative interaction. Contributed Session at the Joint Statistical Meetings. Miami, August 1, 2011.
Invited. Treatment heterogeneity and individual qualitative interaction. National Institute of Environmental Health Sciences, Raleigh, NC. Dec. 14, 2010.
Invited. Topics in high-dimensional data analysis. Seminar at St. Olaf College, Northfield, MN. April 7, 2009.
Modeling the distribution of P-values in high-dimensional applications. Topic Contributed Session at the Joint Statistical Meetings. Denver, August 3, 2008.
Invited. Challenges and approaches to the analysis of high-dimensional data. Ecological Genomics Research Forum. Kansas State University. May 31, 2008.
Invited. Evaluating statistical methods using plasmode data sets: An illustration with the false discovery rate. University of Missouri – Columbia. September 5, 2007.
Invited. Intentional weight-loss effects on mortality rate modeled as a latent variable problem. ENAR section of the Joint Statistical Meetings. Salt Lake City, August 1, 2007.
Invited. Simulating high dimensional data for comparing statistical methods. Spring Research Conference. Ames, Iowa, May 21 – 23, 2007.
Invited. Individual treatment response heterogeneity. Design, Analysis, & Interpretation of RCTs in Obesity (funding provided by NIH). Newark, NJ. December 4 – 5,
2006.
Invited. Multiple testing and the false discovery rate (FDR). The Second Plant Microarray Short Course on Design and Analysis of Plant Microarray Experimentation (funded by NSF). Boston, August 2 – 4, 2006.
Invited. Challenges and Approaches to Analyzing High Dimensional Data. Colloquium talk. University of North Florida, Jacksonville. March 29th, 2006.
Power and type I error in a global test of differential expression. Biometrics section of the Joint Statistical Meetings. Minneapolis, MN August 7-11, 2005.
Modeling P-values in high-dimensional testing applications using a uniform-beta mixture: The performance of interval estimates. The meetings of The International Biometric Society / Eastern North American Region (ENAR).Austin, TX. March 20 – 23, 2005.
Sample size and power assessment in microarray studies. Poster presentation. Conference on Applied Statistics in Agriculture. Kansas State University, Manhattan, KS April 25-27, 2004.
Invited. The distribution of P-values in microarray experiments. Department of Statistics Colloquium. University of Missouri – Columbia. November 21, 2003.
Invited. The distribution of P-values in microarray experiments. International Conference on Statistics, Combinatorics, and Related Areas. University of Southern Maine, Portland, ME. October 3 – 5, 2003.
A Study Evaluating Aerosol Particulate Concentration and Size in the Stratospheric Plumes of Rockets. Statistical Consulting Section of the Joint Statistical Meetings. San Francisco, August 3 – 7, 2003.
Individual treatment effects in randomized trials with binary outcomes. The meetings of The International Biometric Society / Western North American Region (WNAR). Golden, CO June 22 – 25, 2003.
Invited Talk. “Individual treatment heterogeneity in clinical experiments”. Biopharmaceutical Section of the Joint Statistical Meetings. New York, NY. August 11 – 15, 2002.
“The profession of statistics and statistical techniques for microarray data” . Making Sense of Data Workshop for Teachers, an activity based quantitative literacy workshop for elementary, middle school, and high school teachers in Missouri. Summer, 2001.
“An adaptive nonparametric ANCOVA for survey data”. The meetings of The International Biometric Society / Eastern North American Region (ENAR). Chicago, IL. Spring, 2000.
“Unit-treatment interaction in randomized trials with dichotomous responses”. Biometrics section of the Joint Statistical Meetings. Baltimore, MD August 8-12, 1999.
“Evaluating unit-treatment interaction in two randomized designs”. The meetings of The International Biometric Society / Eastern North American Region (ENAR). Atlanta, GA Spring, 1999.
“Estimating a subject by treatment interaction in cross-over designs”. Biopharmaceutical Section of the Joint Statistical Meetings. Dallas, TX August 9-13, 1998.
“Causal Inference and estimating a unit-treatment interaction in randomized experiments”. Conference on Applied Statistics in Agriculture. Kansas State University, Manhattan, KS April 26-28, 1998.
“Causal inference and the problem of estimating a subject by treatment interaction in matched-pairs experiments”. The meetings of The International Biometric Society / Eastern North American Region (ENAR). Pittsburgh, PA Spring, 1998. CV: Page 12
“Inference of cause-effect relationships”. Planning session for the Multiresource Inventory Techniques Project. USDA Forest Service, Fort Collins, CO November 12, 1997.
“Issues concerning estimation of the variance of treatment effects under the Rubin model for causal inference”. Paper presented in a special contributed paper session with Donald B. Rubin as discussant. The Joint Statistical Meetings. Anaheim, CA August 10-14, 1997.
“A generalized method of analysis of covariance using tree-structured regression”. The International Conference on Combinatorics, Information Theory, and Statistics. University of Southern Maine, Portland, Maine. July 18-20, 1997.
(with Jennifer Hoeting) “Model averaging for linear regression models using Bayesian simultaneous variable, outlier, and transformation selection (SVOT)”. Poster presentation at The International Workshop on Model Uncertainty and Model Robustness. Bath, England. June 30 - July 2, 1995.
Informal Talks
Intentional weight loss using potential outcomes and matched-pairs. Research meeting at University of Alabama at Birmingham. Sept 15-16, 2008.
Drawing inferences in high dimensional settings using the distribution of P-values: some cautionary remarks and recent developments. Research meeting: MD Anderson Cancer Center, Houston. February 2008.
Intentional weight loss effects on mortality as a latent variable problem. Research meeting at the Centers for Disease Control, Atlanta. March 2007.
Topics in high dimensional data analysis. Presentation to UMR class, Problem Solving in Applied Mathematics. Fall 2006.
Modeling P-values in multiple testing applications. Annual meeting of the NSF funded Microarray Research Coordination Network. Mohonk Mountain House, New Paltz, NY. September 2005.
Subject – treatment interaction. MAA meeting of undergraduate students. UMR, Fall 2004.
Genes to Outer Space. MAA meeting of undergraduate students. UMR. Fall, 2003.
Power in Microarray Studies. Annual meeting of the NSF funded Microarray Research Coordination Network. Mohonk Mountain House, New Paltz, NY. September 2003.
9. A statistical analysis of microarray data. MAA meeting of undergraduate students. UMR. Fall, 2002.
Analysis of genetic expression data. Graduate Student seminar, Department of Mathematics and Statistics, University of Missouri – Rolla (UMR). Nov. 1, 2001.
First moment ignorability. Statistics seminar series. Department of Mathematics and Statistics, UMR. Fall, 2000.
Causality in statistics. Journal Club. Obesity Research Center, New York NY. July 2000.
Gary Gadbury, Invited. Interdisciplinary statistical research topics and their relevance to the state and society. Presentation to the Dean’s Advisory Council, October 2012, Manhattan, KS.
Invited. Conditional network testing in high-dimensional dependent data. Interface 2012: The Future of Statistical Computing. Houston, May 16 – 18, 2012 (with Dilan Paranagama).
Gary L. Gadbury, Robert Poulson, David Allison. Treatment heterogeneity and individual qualitative interaction. Contributed Session at the Joint Statistical Meetings. Miami, August 1, 2011.
Invited. Treatment heterogeneity and individual qualitative interaction. National Institute of Environmental Health Sciences, Raleigh, NC. Dec. 14, 2010.
Invited. Topics in high-dimensional data analysis. Seminar at St. Olaf College, Northfield, MN. April 7, 2009.
Modeling the distribution of P-values in high-dimensional applications. Topic Contributed Session at the Joint Statistical Meetings. Denver, August 3, 2008.
Invited. Challenges and approaches to the analysis of high-dimensional data. Ecological Genomics Research Forum. Kansas State University. May 31, 2008.
Invited. Evaluating statistical methods using plasmode data sets: An illustration with the false discovery rate. University of Missouri – Columbia. September 5, 2007.
Invited. Intentional weight-loss effects on mortality rate modeled as a latent variable problem. ENAR section of the Joint Statistical Meetings. Salt Lake City, August 1, 2007.
Invited. Simulating high dimensional data for comparing statistical methods. Spring Research Conference. Ames, Iowa, May 21 – 23, 2007.
Invited. Individual treatment response heterogeneity. Design, Analysis, & Interpretation of RCTs in Obesity (funding provided by NIH). Newark, NJ. December 4 – 5,
2006.
Invited. Multiple testing and the false discovery rate (FDR). The Second Plant Microarray Short Course on Design and Analysis of Plant Microarray Experimentation (funded by NSF). Boston, August 2 – 4, 2006.
Invited. Challenges and Approaches to Analyzing High Dimensional Data. Colloquium talk. University of North Florida, Jacksonville. March 29th, 2006.
Power and type I error in a global test of differential expression. Biometrics section of the Joint Statistical Meetings. Minneapolis, MN August 7-11, 2005.
Modeling P-values in high-dimensional testing applications using a uniform-beta mixture: The performance of interval estimates. The meetings of The International Biometric Society / Eastern North American Region (ENAR).Austin, TX. March 20 – 23, 2005.
Sample size and power assessment in microarray studies. Poster presentation. Conference on Applied Statistics in Agriculture. Kansas State University, Manhattan, KS April 25-27, 2004.
Invited. The distribution of P-values in microarray experiments. Department of Statistics Colloquium. University of Missouri – Columbia. November 21, 2003.
Invited. The distribution of P-values in microarray experiments. International Conference on Statistics, Combinatorics, and Related Areas. University of Southern Maine, Portland, ME. October 3 – 5, 2003.
A Study Evaluating Aerosol Particulate Concentration and Size in the Stratospheric Plumes of Rockets. Statistical Consulting Section of the Joint Statistical Meetings. San Francisco, August 3 – 7, 2003.
Individual treatment effects in randomized trials with binary outcomes. The meetings of The International Biometric Society / Western North American Region (WNAR). Golden, CO June 22 – 25, 2003.
Invited Talk. “Individual treatment heterogeneity in clinical experiments”. Biopharmaceutical Section of the Joint Statistical Meetings. New York, NY. August 11 – 15, 2002.
“The profession of statistics and statistical techniques for microarray data” . Making Sense of Data Workshop for Teachers, an activity based quantitative literacy workshop for elementary, middle school, and high school teachers in Missouri. Summer, 2001.
“An adaptive nonparametric ANCOVA for survey data”. The meetings of The International Biometric Society / Eastern North American Region (ENAR). Chicago, IL. Spring, 2000.
“Unit-treatment interaction in randomized trials with dichotomous responses”. Biometrics section of the Joint Statistical Meetings. Baltimore, MD August 8-12, 1999.
“Evaluating unit-treatment interaction in two randomized designs”. The meetings of The International Biometric Society / Eastern North American Region (ENAR). Atlanta, GA Spring, 1999.
“Estimating a subject by treatment interaction in cross-over designs”. Biopharmaceutical Section of the Joint Statistical Meetings. Dallas, TX August 9-13, 1998.
“Causal Inference and estimating a unit-treatment interaction in randomized experiments”. Conference on Applied Statistics in Agriculture. Kansas State University, Manhattan, KS April 26-28, 1998.
“Causal inference and the problem of estimating a subject by treatment interaction in matched-pairs experiments”. The meetings of The International Biometric Society / Eastern North American Region (ENAR). Pittsburgh, PA Spring, 1998. CV: Page 12
“Inference of cause-effect relationships”. Planning session for the Multiresource Inventory Techniques Project. USDA Forest Service, Fort Collins, CO November 12, 1997.
“Issues concerning estimation of the variance of treatment effects under the Rubin model for causal inference”. Paper presented in a special contributed paper session with Donald B. Rubin as discussant. The Joint Statistical Meetings. Anaheim, CA August 10-14, 1997.
“A generalized method of analysis of covariance using tree-structured regression”. The International Conference on Combinatorics, Information Theory, and Statistics. University of Southern Maine, Portland, Maine. July 18-20, 1997.
(with Jennifer Hoeting) “Model averaging for linear regression models using Bayesian simultaneous variable, outlier, and transformation selection (SVOT)”. Poster presentation at The International Workshop on Model Uncertainty and Model Robustness. Bath, England. June 30 - July 2, 1995.
Informal Talks
Intentional weight loss using potential outcomes and matched-pairs. Research meeting at University of Alabama at Birmingham. Sept 15-16, 2008.
Drawing inferences in high dimensional settings using the distribution of P-values: some cautionary remarks and recent developments. Research meeting: MD Anderson Cancer Center, Houston. February 2008.
Intentional weight loss effects on mortality as a latent variable problem. Research meeting at the Centers for Disease Control, Atlanta. March 2007.
Topics in high dimensional data analysis. Presentation to UMR class, Problem Solving in Applied Mathematics. Fall 2006.
Modeling P-values in multiple testing applications. Annual meeting of the NSF funded Microarray Research Coordination Network. Mohonk Mountain House, New Paltz, NY. September 2005.
Subject – treatment interaction. MAA meeting of undergraduate students. UMR, Fall 2004.
Genes to Outer Space. MAA meeting of undergraduate students. UMR. Fall, 2003.
Power in Microarray Studies. Annual meeting of the NSF funded Microarray Research Coordination Network. Mohonk Mountain House, New Paltz, NY. September 2003.
9. A statistical analysis of microarray data. MAA meeting of undergraduate students. UMR. Fall, 2002.
Analysis of genetic expression data. Graduate Student seminar, Department of Mathematics and Statistics, University of Missouri – Rolla (UMR). Nov. 1, 2001.
First moment ignorability. Statistics seminar series. Department of Mathematics and Statistics, UMR. Fall, 2000.
Causality in statistics. Journal Club. Obesity Research Center, New York NY. July 2000.