• PHASE I
    • SAMPLE SIZE CALCULATION
    • PHASE II
    • PHASE I-II
    • Basket Trials
    • Design & Conduct
    • Education
    Integrated Platform
    For Designing
    Clinical Trials
    Research
    .
    Education
    .
    Innovation

Clinical Trial Design Software

BIN
Binary Outcome
Includes the sample size calculation for one, two or more groups.
CON
Continuous Outcome
Includes the sample size calculation for one, two or more groups.
TTE
Time to Event Outcome
Includes log-rank test.
BIS
BOIN for Single Agent
The Bayesian optimal interval (BOIN) design is a novel phase I dose-finding trial design more...
TTB
Time-to-event BOIN
The time-to-event Bayesian optimal interval (TITE-BOIN) design handles more...
BIC
BOIN for Drug Combination
The Bayesian optimal interval (BOIN) drug combination design is a novel phase I dose-finding design more...
CRM
CRM & BMA-CRM
The continual reassessment method (CRM) is a model-based dose-finding approach more...
KB
Keyboard Design
The keyboard design provides an upgrade to the modified toxicity probability more...
S2S
Simon's Two Stage Design
The Simon's two stage design is a commonly used phase II design. It controlls type 1 more...
BOP
Bayesian Optimal Phase 2 (BOP2) Design
The Bayesian optimal phase II (BOP2) design is a flexible Bayesian design that allows more...
PP
Bayesian Efficacy Monitoring with Predictive Probability
Bayesian efficacy monitoring with options of early futility more...
DL
Bayesian Phase 2 Design with Delayed Outcomes
One practical impediment in adaptive phase II trials is that outcomes must be observed soon enough more...
TM
Bayesian Toxicity Monitoring
Bayesian toxicity monitoring for evaluating drug safety.
PO
Bayesian Efficacy Monitoring with Posterior Probability
Bayesian efficacy monitoring with options of early futility and/or efficacy stopping using posterior probability.
OBD
Find Optimal Biological Dose for Immunotherapy
This design is used to find the optimal biological dose (OBD) for molecularly targeted agents and more...
BB1
Bayesian Update for a Beta-Binomial Distribution
An interactive application to show the Bayesian update of a beta-binomial distribution.
BB2
Bayesian Update for Two Beta-Binomial Distributions
An interactive application to show the Bayesian update of two beta-binomial distributions.
NM
Bayesian Update for a Normal Distribution with Known and Unknown Variance
An interactive application to show the Bayesian update of a normal distribution.
DT
Parameter Estimation for A Diagnostic Test
An interactive application to calculate the post-test disease probability given the disease more...
ROC
Varying Cut-Point and Parameter Estimation of the ROC Curve Analysis
An interactive application to calculate the post-test disease probability given the disease prevalence, more...
HMB
Bayesian Hierarchical Model-Binomial Data
An interactive application for Bayesian Hierarchical Model - Binomial Data.
HMN
Bayesian Hierarchical Model-Normal Data
An interactive application for Bayesian Hierarchical Model - Normal Data.
CBH
Calibrated Bayesian Hierarchical Model Design
Bayesian hierarchical modeling has been proposed to adaptively borrow information across cancer more...
BST
Bayesian Latent Subgroup Design for Basket Trials
The innovation of the BLAST design is that it adaptively clusters cancer types within a basket more...
Instructions
1. You can access the software online by clicking on the red circle or the title.
2. You can expand the software description by mousing over the description.
3. You may download a copy of the desktop version of the software by clicking on the download arrow where available.

MEET OUR TEAM

Our research team is comprised of Professors Ying Yuan and J. Jack Lee and their current and former lab members. Our objective is to improve the safety, efficacy, efficiency, and success rate of clinical research and drug development by developing and implementing innovative adaptive clinical trial designs.

Principal Investigators

Ying Yuan, Ph.D., Professor

Dr. Yuan's interest is related to developing new statistical methods and applying them to medical research, especially cancer clinical trials. Specifically, his research interests include the areas below: For more information click here
  • Bayesian adaptive clinical trial designs
  • Statistical analysis of missing data
  • Bayesian modeling and hypothesis testing
  • Mediation analysis for behavioral and social research

J. Jack Lee, Ph.D., M.S., D.D.S., Professor

Dr. Lee has been working on the development and application of innovative Bayesian methods for cancer clinical trials. Participates in multidisciplinary translational research in head/neck and lung cancer teams funded by the NIH and DoD. For more information click here
  • Design and analysis of clinical trials
  • Survival analysis
  • Statistical computation/graphics
  • Incorporation of multiple biomarkers and adaptive designs

Current and Former Lab Members

Dr. Chunyan Cai

Assistant Professor
The University of Texas Health
Science Center at Houston

Dr. Tom Murray

Assistant Professor
School of Public Health
University of Minnesota

Dr. Haitao Pan

Assistant Professor
St. Jude Children's Research
Hospital

Dr. Yong Zang

Assistant Professor
Indiana University School
of Medicine

Dr. Nan Chen

Computational Scientist
The University of Texas
MD Anderson Cancer Center

Dr. Ying-Wei Kuo

Research Programmer
The University of Texas
MD Anderson Cancer Center

Yiyi Chu

Graduate Research Assistant
The University of Texas Health
Science Center at Houston

Rongji Mu

Visiting Ph.D. Student
East China Normal University
(Shanghai, China)

Heng Zhou

Graduate Research Assistant
The University of Texas
MD Anderson Cancer Center

Yanhong Zhou

Graduate Research Assistant
The University of Texas
MD Anderson Cancer Center

Liangcai Zhang

Graduate Research Assistant
Rice Unversity
 

Juan Posadas

Data Integrator
The University of Texas
MD Anderson Cancer Center

Selected Publications

(* supervised PhD students or postdocs)
  1. Book

    Bayesian Designs for Phase I–II Clinical Trials

    • First Edition
    • Authors: Ying Yuan, ‎Hoang Q. Nguyen,‎ and Peter F. Thall
    • ISBN-13: 978-1498709552
    • Chapman & Hall/CRC Biostatistics Series

    Bayesian Adaptive Methods for Clinical Trials

    • First Edition
    • Authors: Scott M. Berry,‎ Bradley P. Carlin,‎ J. Jack Lee,‎ and Peter Muller
    • ISBN-13: 978-143982548
    • Chapman & Hall/CRC Biostatistics Serie, Vol. 38s
  2. Clinical Trial Design

    • Chu, Y.* and Yuan, Y. (2017) BLAST: Bayesian Latent Subgroup Design for Basket Trials Accounting for Patient Heterogeneity. Journal of the Royal Statistical Society: Series C, to appear.
    • Chu, Y.* and Yuan, Y. (2017) A Bayesian Basket Trial Design Using Calibrated Bayesian Hierarchical Model. Clinical Trials, to appear.
    • Liu, S., Guo, B. and Yuan, Y. (2017) A Bayesian Phase I/II Design for Immunotherapy Trials. Journal of the American Statistical Association, to appear.
    • Riviere, M.K., Yuan, Y., Jourdan, J.H., Dubois, F. and Zohar, S. (2017) Phase I/II Dose-Finding Design for Molecularly Targeted Agent: Plateau Determination using Adaptive Randomization. Statistical Methods in Medical Research, to appear.
    • Murray, T.*, Yuan, Y., Thall, P., Elizondo, JH. and Hofstetter, WL. (2017) A Bayesian Utility-Based Stratified Medicine Design for the Effectiveness of Nutritional Prehabilitation in Thoracic Surgery. Biometrics, to appear.
    • Murray, T.*, Yuan, Y. and Thall, P. (2017) A Bayesian Machine Learning Method for Optimizing Dynamic Treatment Regimes. Journal of the American Statistical Association, to appear.
    • Yan, F., Mandrekar, SJ. and Yuan, Y. (2017) Keyboard: A Novel Bayesian Toxicity Probability Interval Design for Phase I Clinical Trials. Clinical Cancer Research, 23, 3994-4003.
    • Zhou, H.*, Lee, JJ. and Yuan, Y. (2017) BOP2: Bayesian Optimal Design for Phase II Clinical Trials with Simple and Complex Endpoints. Statistics in Medicine , 36, 3302-3314.
    • Pan, H.* and Yuan, Y. (2017) A Calibrated Power Prior Approach to Borrow Information from Historical Data with Application to Biosimilar Clinical Trials. Journal of the Royal Statistical Society: Series C , 66, 979-996.
    • Guo, B.* and Yuan, Y. (2017) Bayesian Phase I/II Biomarker-based Dose Finding for Precision Medicine with Molecularly Targeted Agents. Journal of the American Statistical Association, 112, 508-520.
    • Murray, T.*, Thall, P., Yuan, Y., McAvoy, S. and Gomez, D. (2017) Robust treatment comparison based on utilities of semi-competing risks in non-small-cell lung cancer. Journal of the American Statistical Association, 112, 11-23.
    • Zang, Y.* and Yuan, Y. (2017) Optimal Sequential Enrichment Designs for Phase II Clinical Trials. Statistics in Medicine, 36, 54-66.
    • Yuan, Y., Hess, K., Hilsenbeck, S. and Gilbert, M. (2016) Bayesian Optimal Interval Design: A Simple and Well-Performing Design for Phase I Oncology Trials. Clinical Cancer Research, 22, 4291-430.
    • Yuan, Y., Guo, B, Munsell, M., Lu, K. and Jazzari, A. (2016) MIDAS: a practical Bayesian design for platform trials with molecularly targeted agents. Statistics in Medicine, 35, 3892-3906.
    • Zang, Y.*, Liu, S. and Yuan, Y. (2016) Optimal Marker-strategy Clinical Trial Design to Detect Predictive Markers for Targeted Therapy. Biostatistics, 17, 549-560.
    • Zhang, L.* and Yuan, Y. (2016) A Practical Bayesian Design to Identify the Maximum Tolerated Dose Contour for Drug Combination Trials. Statistics in Medicine, 35, 4924-4936.
    • Riviere, M.K.*, Yuan, Y., Jourdan, J.H., Dubois, F. and Zohar, S. (2016) Phase I/II Dose-Finding Design for Molecularly Targeted Agent: Plateau Determination using Adaptive Randomization. Statistical Methods in Medical Research, to appear
    • Chu, Y.*, Pan, H. and Yuan, Y. (2016) Adaptive dose modification for phase I clinical trials. Statistics in Medicine, 35, 3497-508.
    • Iasonos, A. , Wages N., Conaway, M., Cheung, K., Yuan, Y. and O�Quigley, J. (2016) Dimension of Model Parameter Space and Operating Characteristics in Adaptive Dose-Finding Studies. Statistics in Medicine, 35, 3760-3775.
    • Pan, H.* and Yuan, Y. (2016) A Default Method to Specify Skeletons for Bayesian Model Averaging Continual Reassessment Method for Phase I Clinical Trials. Statistics in Medicine, 36, 266-279.
    • Zang, Y.*, J. Lee and Yuan, Y. (2016) Two-stage marker-stratified clinical trial design in the presence of biomarker misclassification. Journal of the Royal Statistical Society: Series C, 65, 585-601.
    • Guo, B., Li, Y. and Yuan, Y. (2016) A dose-schedule-finding design for phase I/II clinical trials. Journal of the Royal Statistical Society: Series C, 65, 259-272.
    • Chen, Z., Yuan, Y., Li, Z., Kutner, M., Owonikoko, T., Curran, W, Khuri, F. and Kowalski, J. (2015) Dose escalation with over-dose and under-dose controls in phase I/II clinical trials. Contemporary Clinical Trials, 43, 133-141.
    • Shen, W.*, Ning, J. and Yuan, Y. (2015) Bayesian sequential monitoring design for clinical trials with non-compliance Statistics in Medicine, 34, 2104-2115.
    • Zang, Y.*, Liu, S. and Yuan, Y. (2015) Optimal Marker-Adaptive Designs for Targeted Therapy Based on Imperfectly Measured Biomarkers. Journal of the Royal Statistical Society: Series C, 64, 635-650.
    • Liu, S. and Yuan, Y. (2015) Bayesian Optimal Interval Designs for Phase I Clinical Trials. Journal of the Royal Statistical Society: Series C, 64, 507-523.
    • Guo, B. and Yuan, Y. (2015) A Bayesian Design for Phase I/II Clinical Trials with Nonignorable Dropout. Statistics in Medicine, 34, 1721-1732.
    • Shen, W.*, Ning, J. and Yuan, Y. (2015) A Direct Method to Evaluate the Time-dependent Predictive Accuracy for Biomarkers. Biometrics, 71, 439-449.

    • Liu, S., Pan, H., Huang Q., Xia, J. and Yuan, Y. (2015) Bridging Continual Reassessment Method for Phase I Clinical Trials in Different Ethnic Populations. Statistics in Medicine, 10, 1681-1694.
    • Riviere, M.K.*, Yuan, Y., Dubois, F. and Zohar, S. (2015) A Bayesian Dose-finding Design for Clinical Trials Combining a Cytotoxic Agent with a Molecularly Targeted Agent. Journal of the Royal Statistical Society: Series C, 64, 215-229.
    • Jin, I.H.*, Liu, S., Thall, P. and Yuan, Y. (2014) Using Data Augmentation to Facilitate Conduct of Phase I/II Clinical Trials with Delayed Outcomes. Journal of the American Statistical Association, 109, 525-536.
    • Riviere M.K., Yuan Y. , Dubois F. and Zohar S. (2014) A Bayesian dose-finding design for drug combination clinical trials based on the logistic model. Pharmaceutial Statistics, 13, 247-257.
    • Zang, Y.*, Lee J. and Yuan, Y. (2014) Adaptive designs for identifying optimal biological dose for molecularly targeted agents. Clinical Trials, 11, 319-327.
    • Cai, C.*, Liu, S. and Yuan, Y. (2014) A Bayesian Design for Phase II Clinical Trials with Delayed Responses Based on Multiple Imputation. Statistics in Medicine, 33, 4017-4028.
    • Liu, S., Yuan, Y. , Castillo, R., Guerrero, T. and Johnson, V.E. (2014) Evaluation of Deformable Image Registration Spatial Accuracy Using a Bayesian Hierarchical Model. Biometrics, 70, 366-377.
    • Cai, C.*, Yuan, Y. and Ji, Y. (2014) A Bayesian Phase I/II Design for Oncology Clinical Trials of Combining Biological Agents. Journal of the Royal Statistical Society: Series C, 63, 159-173.
    • Liu, S., Yin, G. and Yuan, Y. (2013) Bayesian Data Augmentation Dose Finding with Continual Reassessment Method and Delayed Toxicity. Annals of Applied Statistics, 4, 2138-2156.
    • Ahn, J.*, Yuan, Y., Parmigiani, G., Suraokar, M. B., Diao, L., Wistuba, I. and Wang W. (2013) DeMix: Deconvolution for mixed cancer transcriptomes using raw measured data. Bioinformatics, 29, 1865-1871.
    • Cai, C.*, Yuan, Y. and Johnson, V.E. (2013) Bayesian adaptive phase II screening design for combination trials. Clinical Trials, 10, 353-362.
    • Jin, I.H.*, Yuan, Y. and Liang, F. (2013) Bayesian analysis for exponential random graph models using the adaptive exchange sampler. Statistics and Its Interface, 6, 559-576.
    • Zang, Y*. and Yuan, Y. (2013) A Shrinkage Method for Testing the Hardy-Weinberg Equilibrium in Case-Control Studies. Genetic Epidemiology, 37, 743-750.
    • Yuan, Y., Thall, P. andWolf, J. (2012) Estimating Progression-free Survival When the Progression Status of Some Subjects is Unknown. Journal of the Royal Statistical Society: Series C, 61, 135-149.

    • Yuan, Y. and Johnson, V.E. (2012) Goodness-of-Fit Diagnostics for Bayesian Hierarchical Models. Biometrics 68, 156-164.
    • Huo, L.*, Yuan, Y. and Yin, G. (2012) Dose Finding in Drug Combinations with Discrete and Continuous Doses. Bayesian Analysis, 7, 235-252.
    • Yuan, Y. and Yin, G. (2011) Robust EM Continual Reassessment Method in Oncology Dose Finding. Journal of the American Statistical Association 106, 818-831. (featured article)
    • Lei, X., Yuan, Y. and Yin, G. (2011) Bayesian phase II adaptive randomization by jointly modeling time-to-event efficacy and binary toxicity. Lifetime Data Analysis 17, 156-174.
    • Yuan, Y. and Yin, G. (2011) Bayesian phase I/II drug-combination trial design in oncology. Annals of Applied Statistics, 5, 924-942.
    • Yuan, Y. and Yin, G. (2011) Bayesian Hybrid Design in Phase I Oncology Clinical Trials. Statistics in Medicine, 30, 2098-2108.
    • Yuan, Y., Huang, X. and Liu, S. (2011) A Bayesian response-adaptive covariate-balanced randomization design for clinical trials. Statistics in Medicine, 30, 1218-1229.
    • Yuan, Y. and Yin, G. (2011) On adaptive randomization: is it useful? Journal of Clinical Oncology, 29, e390-e392
    • Yin, G., Ma, Y., Liang, F. and Yuan, Y. (2011) Stochastic generalized method of moments. Journal of Computational and Graphical Statistics 20, 714-727.
    • Yuan, Y. and Yin, G. (2011) Dose-response curve estimation: A semiparametric mixture approach. Biometrics 67, 1543-1554.
    • Yin, G. and Yuan, Y. (2009) Bayesian Model Averaging Continual Reassessment Method in Phase I Clinical Trials. Journal of the American Statistical Association 104, 954-968.
    • Song P.X., Li, M. and Yuan, Y. (2009) Joint Regression Analysis of Correlated Data Using Gaussian Copulas. Biometrics 65, 60-68.
    • Yin, G. and Yuan, Y. (2009) A latent contingency table approach to dose-finding for combinations of two agents. Biometrics 65, 866-875.
    • Yin, G. and Yuan, Y. (2009) Bayesian Dose-finding in Oncology for Drug Combinations by Copula Regression. Journal of the Royal Statistical Society: Series C 58, 211-224.
    • Yuan, Y. and Yin, G. (2009) Bayesian Dose-finding by Jointly Modeling Toxicity and Efficacy as Time-to-Event Outcomes. Journal of the Royal Statistical Society: Series C 58, 719-736.
    • Yuan, Y. and Johnson, V.E. (2008) Bayesian Hypothesis Tests Using Nonparametric Statistics. Statistica Sinica 18, 1185-1200
    • Yuan, Y. and Yin, G. (2008) Sequential Continual Reassessment Method for Two-dimensional Dose Finding. Statistics in Medicine 27, 5664-5678.
    • Lee JJ, Liu DD. A predictive probability design for phase II cancer clinical trials. Clin Trials 5(2):93-106, 2008. PMID: 18375647.
    • Zhou X, Liu S, Kim ES, Herbst RS, Lee JJ. Bayesian adaptive design for targeted therapy development in lung cancer--a step toward personalized medicine. Clin Trials 5(3):181-93, 2008. PMID: 18559407.
    • Le Tourneau C, Lee JJ, Siu LL. Dose escalation methods in phase I cancer clinical trials. J Natl Cancer Inst 101(10):708-20, 5/2009. e-Pub 5/2009. PMCID: PMC2684552.
    • Biswas S, Liu DD, Lee JJ, Berry DA. Bayesian clinical trials at the University of Texas MD Anderson Cancer Center. Clin Trials 6(3):205-16, 6/2009. PMCID: PMC2913209.
    • Cao J, Lee JJ, Alber S. Comparison of Bayesian sample size criteria: ACC, ALC, and WOC. J Stat Plan Inference 139(12):4111-4122, 12/2009. PMCID: PMC4279958.
    • Lee JJ, Xuemin Gu , Suyu Liu. Bayesian adaptive randomization designs for targeted agent development. Clin Trials 7(5):584-96, 10/2010. e-Pub 6/2010. PMCID: PMC5110207.
    • Gu X, Lee JJ. A simulation study for comparing testing statistics in response-adaptive randomization. BMC Med Res Methodol 10(48):48, 2010. e-Pub 6/2010. PMCID: PMC2911470.
    • Lee JJ. Demystify statistical significance--time to move on from the p value to bayesian analysis. J Natl Cancer Inst 103(1):2-3, 1/2011. e-Pub 12/2010. PMID: 21131578.
    • Yin G, Chen N, Lee JJ. Phase II trial design with Bayesian adaptive randomization and predictive probability. J R Stat Soc Ser C Appl Stat 61(2):219-35, 3/2012. PMCID: PMC3832255.
    • Lee JJ, Chen N, Yin G. Worth adapting? Revisiting the usefulness of outcome-adaptive randomization. Clin Cancer Res 18(17):4498-507, 9/2012. e-Pub 7/2012. PMCID: PMC3495976.
    • Lee JJ, Chu CT. Bayesian clinical trials in action. Stat Med 31(25):2955-72, 11/2012. e-Pub 6/2012. PMCID: PMC3495977.
    • Jiang F, Lee JJ, Müller P. A Bayesian decision-theoretic sequential response-adaptive randomization design. Stat Med 32(12):1975-1994, 5/2013. e-Pub 1/2013. PMCID: PMC3873748.
    • Chen N, Lee JJ. Optimal continuous-monitoring design of single-arm phase ii trial based on the simulated annealing method. Contemp Clin Trials 35(1):170-178, 5/2013. e-Pub 3/2013. PMCID: PMC3741066.
    • Yao JC, Meric-Bernstam F, Lee JJ, Eckhardt SG. Accelerated approval and breakthrough therapy designation: oncology drug development on speed? Clin Cancer Res 19(16):4305-4308, 8/2013. e-Pub 7/2013. PMCID: PMC4167364.
    • Gu X, Yin G, Lee JJ. Bayesian two-step Lasso strategy for biomarker selection in personalized medicine development for time-to-event endpoints. Contemp Clin Trials 36(2):642-50, 11/2013. e-Pub 9/2013. PMCID: PMC3873734.
    • Kim MO, Liu C, Hu F, Lee JJ. Outcome-adaptive randomization for a delayed outcome with a short-term predictor: imputation-based designs. Stat Med 33(23):4029-42, 10/2014. e-Pub 5/2014. PMCID: PMC4159410.
    • Zang Y, Lee JJ. Adaptive clinical trial designs in oncology. Chin Clin Oncol 3(4):49, 12/2014. PMID: 25841530.
    • Marchenko, O., Fedorov, V., Lee, J.J., Nolan, C., Pinheiro, J. Adaptive Clinical Trials: Overview of Early-Phase Designs and Challenges. Therapeutic Innovation and Regulatory Science 48(1):20-30, 2014.
    • Alber, S. A., Lee, J. J. Calibrating the prior distribution for a normal model with conjugate prior. Journal of Statistical Computation and Simulation:1-21, 2014.
    • Du Y, Wang X, Lee JJ. Simulation study for evaluating the performance of response-adaptive randomization. Contemp Clin Trials 40:15-25, 1/2015. e-Pub 11/2014. PMCID: PMC4314433.
    • Liu S, Lee JJ. An overview of the design and conduct of the BATTLE trials. Chin Clin Oncol 4(3):33, 9/2015. PMID: 26408300.
    • Halperin DM, Lee JJ, Dagohoy CG, Yao JC. Rational Clinical Experiment: Assessing Prior Probability and Its Impact on the Success of Phase II Clinical Trials. J Clin Oncol 33(26):2914-9, 9/2015. e-Pub 8/2015. PMCID: PMC4554752.
    • Lee JJ. Commentary on Hey and Kimmelman. Clin Trials 12(2):110-2, 4/2015. e-Pub 2/2015. PMCID: PMC4492278.
    • Hobbs BP, Chen N, Lee JJ. Controlled multi-arm platform design using predictive probability. Stat Methods Med Res. e-Pub 1/2016. PMCID: PMC5039108.
    • Gu X, Chen N, Wei C, Liu S, Papadimitrakopoulou VA, Herbst RS, Lee JJ. Bayesian Two-Stage Biomarker-Based Adaptive Design for Targeted Therapy Development. Stat Biosci 8((1)):99-128, 6/2016. e-Pub 12/2014. PMCID: PMC5014437.
    • Zang Y, Lee JJ. A robust two-stage design identifying the optimal biological dose for phase I/II clinical trials. Stat Med 36(1):27-42, 1/2017. e-Pub 8/2016. PMCID: PMC5138134.
    • Du Y, Cook JD, Lee JJ. Comparing three regularization methods to avoid extreme allocation probability in response-adaptive randomization. J Biopharm Stat:1-11. e-Pub 2/2017. PMID: 28323532.
    • Kim S, Baladandayuthapani V, Lee JJ. Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression. Stat Biosci 9(1):217-245, 6/2017. e-Pub 9/2016. PMCID: PMC5543994.
    • Jiang F, Ma Y, Lee, JJ. A second-order semiparametric method for survival analysis, with application to an acquired immune deficiency syndrome clinical trial study. Journal of the Royal Statistical Society Series C: Applied Statistics 66(4):833-846, 2017.
    • Yin G, Chen N, Lee JJ. Bayesian Adaptive Randomization and Trial Monitoring with Predictive Probability for Time-to-Event Endpoint. Statistics in Biosciences:1-19, 2017.
  3. Missing Data Analysis

    • Ahn, J.*, Liu, S., Wang W. and Yuan, Y. (2013) Bayesian Latent-class Mixed-effect Hybrid Models for Dyadic Longitudinal Data with Non-ignorable Dropouts. Biometrics, 69, 914-924.
    • Zhang G. and Yuan, Y. (2012) Modeling Longitudinal Dyadic Data with Nonignorable Dropout with Application to a Breast Cancer Study. Annals of Applied Statistics, 6, 753-771.
    • Yuan, Y. and Yin, G. (2010). Quantile regression for longitudinal studies with nonignorable missing data. Biometrics, 66, 105-114.
    • Yuan, Y. and Little, R.J.A. (2009) Meta-analysis of studies with missing data. Biometrics 65, 487-496.
    • Yuan, Y. and Little, R.J.A. (2009) Mixed-effect hybrid models for longitudinal data with nonignorable dropout. Biometrics 65, 478-486. Yuan, Y., and Little, R.J.A. (2007) Model-Based Estimates of the Finite Population Mean for Two-Stage Cluster Samples with Unit Non-response. Journal of the Royal Statistical Society: Series C 56, 79-97.
    • Yuan, Y., and Little, R.J.A. (2007) Parametric and Semiparametric Model-based Estimates of the Finite Population Mean for Two-Stage Cluster Samples with Item Nonresponse. Biometrics 63, 1172-1180.
  4. Mediation Analysis

    • Huang, J.* and Yuan, Y. (2016) Bayesian Dynamic Mediation Analysis, Psychological Methods, to appear.
    • Yuan, Y. and MacKinnon D. (2014) Robust mediation analysis based on mediation regression. Psychological Methods, 19, 1-20.
    • Yuan, Y. and MacKinnon D. (2009) Bayesian mediation analysis. Psychological Methods, 14, 301-322.

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