Bio

Academic Appointments


Administrative Appointments


  • Director, Financial and Risk Modeling Institute,, Stanford University (2012 - Present)
  • International Advisory Committee Member, Mathematical Sciences Center, Tsinghua University (2012 - Present)
  • Advisory Committee Member, Institute of Mathematical Research, University of Hong Kong (2011 - Present)
  • Chair, Pao-Lu Hsu Distinguished Lecture Series in Statistics and Probability, Center for Mathematical Sciences, Tsinghua University (2011 - Present)
  • International Advisory Committee Member, Center for Statistical Sciences, Peking University (2010 - Present)
  • Co-director, Center for Innovative Study Design, Stanford School of Medicine (2009 - Present)
  • Professor, by courtesy, of the Institute of Computational and Mathematical Engineering, Stanford School of Engineering (2009 - Present)
  • Professor, by courtesy, of Health Research and Policy, Stanford School of Medicine (2007 - Present)
  • Steering Committee, Methods of Analysis Program in the Social Sciences, Stanford University (2005 - Present)
  • Co-director, Biostatistics Core, Stanford University Cancer Center (2004 - Present)
  • Chair, School of Statistics, Chinese Academy of Sciences (2003 - Present)
  • Director, Interdisciplinary Program in Financial Mathematics, Stanford University (1999 - Present)

Honors & Awards


  • Saw Swee Hock Lecture in Statistics, University of Hong Kong (2012)
  • Pao-Lu Hsu Lecture in Statistics, Peking University (2010)
  • Abraham Wald Prize, Sequential Analysis: Design Methods & Applications (2005)
  • Fellow, Center for Advanced Study in Behavioral Sciences (1999)
  • Member, Academia Sinica (1994)
  • COPSS Award, Committee of Presidents of Statistical Societies (1983)
  • Fellow, John Simon Guggenheim Foundation (1983)

Professional Education


  • B.A. with First Class Honors, University of Hong Kong, Mathematics (1967)
  • M.A., Columbia University, Mathematical Statistics (1970)
  • Ph.D., Columbia University, Mathematical Statistics (1971)

Research & Scholarship

Current Research and Scholarly Interests


Lai is widely recognized as a prolific leader in the field of sequential statistical analysis. Among his principal achievements is the development of a comprehensive theory of sequential tests of composite hypotheses, unifying previous approaches and providing far-reaching extensions to cope with the practical complexities that arise in the applications to group sequential clinical trials. In particular, this theory paved the way for his ground-breaking work with Shih on flexible and nearly-optimal group sequential tests that can “self-tune” to the unknown parameters during the course of the trial, under pre-specified constraints on the maximum sample size and significance level.

Other major breakthroughs include (a) accurate confidence intervals following sequential tests by using an innovative resampling approach, (b) a definitive solution to the long-standing “multi-armed bandit problem”, and (c) the development of statistically and computationally efficient sequential change-point detection procedures in multivariate time series and stochastic systems, for applications to industrial quality control, fault detection in engineering systems and segmentation in computational biology.

Besides sequential analysis, Lai has also made ground-breaking contributions to (i) stochastic approximation and recursive estimation, (ii) adaptive control of linear stochastic systems and Markov decision processes, (iii) saddlepoint approximations and boundary-crossing probabilities in Markov random walks and random fields, and (iv) survival analysis, in particular, rand- and M-estimators in regression models when the response variable is subject to censoring and truncation, and interim analysis of clinical trials with failure-time endpoints.

Teaching

2014-15 Courses


Publications

Journal Articles


  • ABO Mismatch Is Associated with Increased Nonrelapse Mortality after Allogeneic Hematopoietic Cell Transplantation BIOLOGY OF BLOOD AND MARROW TRANSPLANTATION Logan, A. C., Wang, Z., Alimoghaddam, K., Wong, R. M., Lai, T., Negrin, R. S., Grumet, C., Logan, B. R., Zhang, M., Spellman, S. R., Lee, S. J., Miklos, D. B. 2015; 21 (4): 746-754

    Abstract

    We evaluated ABO associated outcomes in 1737 patients who underwent allogeneic hematopoietic cell transplantation (allo-HCT) at Stanford University between January 1986 and July 2011. Grafts were 61% ABO matched, 18% major mismatched (MM), 17% minor MM, and 4% bidirectional MM. Median follow-up was 6 years. In multivariate analysis, overall survival (OS) was inferior in minor MM hematopoietic cell transplantations (median 2.1 versus 6.3 years; hazard ratio [HR], 1.56; 95% confidence interval [CI], 1.19 to 2.05; P = .001) in comparison with ABO-matched grafts. ABO minor MM was associated with an increase in early nonrelapse mortality (NRM) (18% versus 13%; HR, 1.48; 95% CI, 1.06 to 2.06; P = .02). In an independent Center for International Blood and Marrow Transplant Research (CIBMTR) analysis of 435 lymphoma patients receiving mobilized peripheral blood grafts, impairment of OS (HR, 1.55; 95% CI, 1.07 to 2.25; P = .021) and increased NRM (HR, 1.72; 95% CI, 1.11 to 2.68; P = .03) were observed in recipients of ABO minor-MM grafts. A second independent analysis of a CIBMTR data set including 5179 patients with acute myeloid leukemia and myelodysplastic syndrome identified a nonsignificant trend toward decreased OS in recipients of ABO minor-MM grafts and also found ABO major MM to be significantly associated with decreased OS (HR, 1.19; 95% CI, 1.08 to 1.31; P < .001) and increased NRM (HR, 1.23; 95% CI, 1.08 to 1.4; P = .002). ABO minor and major MM are risk factors for worse transplantation outcomes, although the associated hazards may not be uniform across different transplantation populations. Further study is warranted to determine which patient populations are at greatest risk, and whether this risk can be modified by anti-B cell therapy or other peri-transplantation treatments.

    View details for DOI 10.1016/j.bbmt.2014.12.036

    View details for Web of Science ID 000351790300025

    View details for PubMedID 25572032

  • ASYMPTOTICALLY EFFICIENT PARAMETER ESTIMATION IN HIDDEN MARKOV SPATIO-TEMPORAL RANDOM FIELDS STATISTICA SINICA Lai, T. L., Lim, J. 2015; 25 (1): 403-421
  • DYNAMIC EMPIRICAL BAYES MODELS AND THEIR APPLICATIONS TO LONGITUDINAL DATA ANALYSIS AND PREDICTION STATISTICA SINICA Lai, T. L., Su, Y., Sun, K. H. 2014; 24 (4): 1505-1528
  • Discussion on "Sequential Estimation for Time Series Models" by T. N. Sriram and Ross Iaci SEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS Lai, T. L. 2014; 33 (2): 169-173
  • A GENERAL THEORY OF PARTICLE FILTERS IN HIDDEN MARKOV MODELS AND SOME APPLICATIONS ANNALS OF STATISTICS Chan, H. P., Lai, T. L. 2013; 41 (6): 2877-2904

    View details for DOI 10.1214/13-AOS1172

    View details for Web of Science ID 000330204900007

  • Group sequential designs for developing and testing biomarker-guided personalized therapies in comparative effectiveness research. Contemporary clinical trials Lai, T. L., Liao, O. Y., Kim, D. W. 2013; 36 (2): 651-663

    Abstract

    Biomarker-guided personalized therapies offer great promise to improve drug development and improve patient care, but also pose difficult challenges in designing clinical trials for the development and validation of these therapies. We first give a review of the existing approaches, briefly for clinical trials in new drug development and in more detail for comparative effectiveness trials involving approved treatments. We then introduce new group sequential designs to develop and test personalized treatment strategies involving approved treatments.

    View details for DOI 10.1016/j.cct.2013.08.007

    View details for PubMedID 23994669

  • Group sequential designs for developing and testing biomarker-guided personalized therapies in comparative effectiveness research. Contemporary clinical trials Lai, T. L., Liao, O. Y., Kim, D. W. 2013; 36 (2): 651-663

    Abstract

    Biomarker-guided personalized therapies offer great promise to improve drug development and improve patient care, but also pose difficult challenges in designing clinical trials for the development and validation of these therapies. We first give a review of the existing approaches, briefly for clinical trials in new drug development and in more detail for comparative effectiveness trials involving approved treatments. We then introduce new group sequential designs to develop and test personalized treatment strategies involving approved treatments.

    View details for DOI 10.1016/j.cct.2013.08.007

    View details for PubMedID 23994669

  • STOCHASTIC CHANGE-POINT ARX-GARCH MODELS AND THEIR APPLICATIONS TO ECONOMETRIC TIME SERIES STATISTICA SINICA Lai, T. L., Xing, H. 2013; 23 (4): 1573-1594
  • RARE-EVENT SIMULATION OF HEAVY-TAILED RANDOM WALKS BY SEQUENTIAL IMPORTANCE SAMPLING AND RESAMPLING ADVANCES IN APPLIED PROBABILITY Chan, H. P., Deng, S., Lai, T. 2012; 44 (4): 1173-1196
  • Sequential design of phase II-III cancer trials STATISTICS IN MEDICINE Lai, T. L., Lavori, P. W., Shih, M. 2012; 31 (18): 1944-1960

    Abstract

    Although traditional phase II cancer trials are usually single arm, with tumor response as endpoint, and phase III trials are randomized and incorporate interim analyses with progression-free survival or other failure time as endpoint, this paper proposes a new approach that seamlessly expands a randomized phase II study of response rate into a randomized phase III study of time to failure. This approach is based on advances in group sequential designs and joint modeling of the response rate and time to event. The joint modeling is reflected in the primary and secondary objectives of the trial, and the sequential design allows the trial to adapt to increase in information on response and survival patterns during the course of the trial and to stop early either for conclusive evidence on efficacy of the experimental treatment or for the futility in continuing the trial to demonstrate it, on the basis of the data collected so far.

    View details for DOI 10.1002/sim.5346

    View details for Web of Science ID 000306471100004

    View details for PubMedID 22422502

  • Clinical trial designs for testing biomarker-based personalized therapies CLINICAL TRIALS Lai, T. L., Lavori, P. W., Shih, M. I., Sikic, B. I. 2012; 9 (2): 141-154

    Abstract

    Advances in molecular therapeutics in the past decade have opened up new possibilities for treating cancer patients with personalized therapies, using biomarkers to determine which treatments are most likely to benefit them, but there are difficulties and unresolved issues in the development and validation of biomarker-based personalized therapies. We develop a new clinical trial design to address some of these issues. The goal is to capture the strengths of the frequentist and Bayesian approaches to address this problem in the recent literature and to circumvent their limitations.We use generalized likelihood ratio tests of the intersection null and enriched strategy null hypotheses to derive a novel clinical trial design for the problem of advancing promising biomarker-guided strategies toward eventual validation. We also investigate the usefulness of adaptive randomization (AR) and futility stopping proposed in the recent literature.Simulation studies demonstrate the advantages of testing both the narrowly focused enriched strategy null hypothesis related to validating a proposed strategy and the intersection null hypothesis that can accommodate to a potentially successful strategy. AR and early termination of ineffective treatments offer increased probability of receiving the preferred treatment and better response rates for patients in the trial, at the expense of more complicated inference under small-to-moderate total sample sizes and some reduction in power.The binary response used in the development phase may not be a reliable indicator of treatment benefit on long-term clinical outcomes. In the proposed design, the biomarker-guided strategy (BGS) is not compared to 'standard of care', such as physician's choice that may be informed by patient characteristics. Therefore, a positive result does not imply superiority of the BGS to 'standard of care'. The proposed design and tests are valid asymptotically. Simulations are used to examine small-to-moderate sample properties.Innovative clinical trial designs are needed to address the difficulties and issues in the development and validation of biomarker-based personalized therapies. The article shows the advantages of using likelihood inference and interim analysis to meet the challenges in the sample size needed and in the constantly evolving biomarker landscape and genomic and proteomic technologies.

    View details for DOI 10.1177/1740774512437252

    View details for Web of Science ID 000302636500001

    View details for PubMedID 22397801

  • Futility stopping in clinical trials STATISTICS AND ITS INTERFACE He, P., Lai, T. L., Liao, O. Y. 2012; 5 (4): 415-423
  • Efficient Adaptive Randomization and Stopping Rules in Multi-arm Clinical Trials for Testing a New Treatment SEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS Lai, T. L., Liao, O. Y. 2012; 31 (4): 441-457
  • Adaptive Trial Designs ANNUAL REVIEW OF PHARMACOLOGY AND TOXICOLOGY, VOL 52 Lai, T. L., Lavori, P. W., Shih, M. 2012; 52: 101-110

    Abstract

    We review adaptive designs for clinical trials, giving special attention to the control of the Type I error in late-phase confirmatory trials, when the trial planner wishes to adjust the final sample size of the study in response to an unblinded analysis of interim estimates of treatment effects. We point out that there is considerable inefficiency in using the adaptive designs that employ conditional power calculations to reestimate the sample size and that maintain the Type I error by using certain weighted test statistics. Although these adaptive designs have little advantage over familiar group-sequential designs, our review also describes recent developments in adaptive designs that are both flexible and efficient. We also discuss the use of Bayesian designs, when the context of use demands control over operating characteristics (Type I and II errors) and correction of the bias of estimated treatment effects.

    View details for DOI 10.1146/annurev-pharmtox-010611-134504

    View details for Web of Science ID 000301839600006

    View details for PubMedID 21838549

  • Sequential Importance Sampling and Resampling for Dynamic Portfolio Credit Risk OPERATIONS RESEARCH Deng, S., Giesecke, K., Lai, T. L. 2012; 60 (1): 78-91
  • A SEQUENTIAL MONTE CARLO APPROACH TO COMPUTING TAIL PROBABILITIES IN STOCHASTIC MODELS ANNALS OF APPLIED PROBABILITY Chan, H. P., Lai, T. L. 2011; 21 (6): 2315-2342

    View details for DOI 10.1214/10-AAP758

    View details for Web of Science ID 000298249900009

  • EVALUATING PROBABILITY FORECASTS ANNALS OF STATISTICS Lai, T. L., Gross, S. T., Shen, D. B. 2011; 39 (5): 2356-2382

    View details for DOI 10.1214/11-AOS902

    View details for Web of Science ID 000299186500007

  • A STEPWISE REGRESSION METHOD AND CONSISTENT MODEL SELECTION FOR HIGH-DIMENSIONAL SPARSE LINEAR MODELS STATISTICA SINICA Ing, C., Lai, T. L. 2011; 21 (4): 1473-1513
  • CRAMER TYPE MODERATE DEVIATIONS FOR STUDENTIZED U-STATISTICS ESAIM-PROBABILITY AND STATISTICS Lai, T. L., Shao, Q., Wang, Q. 2011; 15: 168-179

    View details for DOI 10.1051/ps/2009014

    View details for Web of Science ID 000300777300008

  • Discussion on "Two-Stage Procedures for High-Dimensional Data" by Makoto Aoshima and Kazuyoshi Yata SEQUENTIAL ANALYSIS-DESIGN METHODS AND APPLICATIONS Ing, C., Lai, T. L. 2011; 30 (4): 404-411
  • Sequential generalized likelihood ratio tests for vaccine safety evaluation STATISTICS IN MEDICINE Shih, M., Lai, T. L., Heyse, J. F., Chen, J. 2010; 29 (26): 2698-2708

    Abstract

    The evaluation of vaccine safety involves pre-clinical animal studies, pre-licensure randomized clinical trials, and post-licensure safety studies. Sequential design and analysis are of particular interest because they allow early termination of the trial or quick detection that the vaccine exceeds a prescribed bound on the adverse event rate. After a review of the recent developments in this area, we propose a new class of sequential generalized likelihood ratio tests for evaluating adverse event rates in two-armed pre-licensure clinical trials and single-armed post-licensure studies. The proposed approach is illustrated using data from the Rotavirus Efficacy and Safety Trial. Simulation studies of the performance of the proposed approach and other methods are also given.

    View details for DOI 10.1002/sim.4036

    View details for Web of Science ID 000284023800004

    View details for PubMedID 20799244

  • Multistage Tests of Multiple Hypotheses COMMUNICATIONS IN STATISTICS-THEORY AND METHODS Bartroff, J., Lai, T. L. 2010; 39 (8-9): 1597-1607
  • Theory and applications of multivariate self-normalized processes STOCHASTIC PROCESSES AND THEIR APPLICATIONS de la Pena, V. H., Klass, M. J., Lai, T. L. 2009; 119 (12): 4210-4227
  • Modern sequential analysis and its applications to computerized adaptive testing PSYCHOMETRIKA Bartroff, J., Finkelman, M., Lai, T. L. 2008; 73 (3): 473-486
  • Stochastic segmentation models for array-based comparative genomic hybridization data analysis BIOSTATISTICS Lai, T. L., Xing, H., Zhang, N. 2008; 9 (2): 290-307

    Abstract

    Array-based comparative genomic hybridization (array-CGH) is a high throughput, high resolution technique for studying the genetics of cancer. Analysis of array-CGH data typically involves estimation of the underlying chromosome copy numbers from the log fluorescence ratios and segmenting the chromosome into regions with the same copy number at each location. We propose for the analysis of array-CGH data, a new stochastic segmentation model and an associated estimation procedure that has attractive statistical and computational properties. An important benefit of this Bayesian segmentation model is that it yields explicit formulas for posterior means, which can be used to estimate the signal directly without performing segmentation. Other quantities relating to the posterior distribution that are useful for providing confidence assessments of any given segmentation can also be estimated by using our method. We propose an approximation method whose computation time is linear in sequence length which makes our method practically applicable to the new higher density arrays. Simulation studies and applications to real array-CGH data illustrate the advantages of the proposed approach.

    View details for DOI 10.1093/biostatistics/kxm031

    View details for Web of Science ID 000254293400007

    View details for PubMedID 17855472

  • A Hidden Markov Filtering Approach to Multiple Change-point Models 47TH IEEE CONFERENCE ON DECISION AND CONTROL, 2008 (CDC 2008) Lai, T. L., Xing, H. 2008: 1914-1919
  • Statistical models for the Basel II internal ratings-based approach to measuring credit risk of retail products STATISTICS AND ITS INTERFACE Lai, T. L., Wong, S. P. 2008; 1 (2): 229-241
  • Corrected random walk approximations to free boundary problems in optimal stopping ADVANCES IN APPLIED PROBABILITY Lai, T. L., Yao, Y., Aitsahlia, F. 2007; 39 (3): 753-775
  • Efficient importance sampling for Monte Carlo evaluation of exceedance probabilities ANNALS OF APPLIED PROBABILITY Chan, H. P., Lai, T. L. 2007; 17 (2): 440-473
  • A combined superiority and non-inferiority approach to multiple endpoints in clinical trials STATISTICS IN MEDICINE Bloch, D. A., Lai, T. L., Su, Z., Tubert-Bitter, P. 2007; 26 (6): 1193-1207

    Abstract

    Treatment comparisons in clinical trials often involve multiple endpoints. By making use of bootstrap tests, we develop a new non-parametric approach to multiple-endpoint testing that can be used to demonstrate non-inferiority of a new treatment for all endpoints and superiority for some endpoint when it is compared to an active control. It is shown that this approach does not incur a large multiplicity cost in sample size to achieve reasonable power and that it can incorporate complex dependencies in the multivariate distributions of all outcome variables for the two treatments via bootstrap resampling.

    View details for DOI 10.1002/sim.2611

    View details for Web of Science ID 000244903400002

    View details for PubMedID 16791905

  • Nonparametric functionals of spectral distributions and their applications to time series analysis JOURNAL OF STATISTICAL PLANNING AND INFERENCE Lai, T. L., Xing, H. 2007; 137 (3): 1066-1075
  • Marginal regression analysis of longitudinal data with time-dependent covariates: a generalized method-of-moments approach JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY Lai, T. L., Small, D. 2007; 69: 79-99
  • Identification and adaptive control of change-point ARX models via Rao-Blackwellized particle filters IEEE TRANSACTIONS ON AUTOMATIC CONTROL Chen, Y., Lai, T. L. 2007; 52 (1): 67-72
  • Confidence intervals for survival quantiles in the Cox regression model LIFETIME DATA ANALYSIS Lai, T. L., Su, Z. 2006; 12 (4): 407-419

    Abstract

    Median survival times and their associated confidence intervals are often used to summarize the survival outcome of a group of patients in clinical trials with failure-time endpoints. Although there is an extensive literature on this topic for the case in which the patients come from a homogeneous population, few papers have dealt with the case in which covariates are present as in the proportional hazards model. In this paper we propose a new approach to this problem and demonstrate its advantages over existing methods, not only for the proportional hazards model but also for the widely studied cases where covariates are absent and where there is no censoring. As an illustration, we apply it to the Stanford Heart Transplant data. Asymptotic theory and simulation studies show that the proposed method indeed yields confidence intervals and bands with accurate coverage errors.

    View details for DOI 10.1007/s10985-006-9024-y

    View details for Web of Science ID 000242998200002

    View details for PubMedID 17053975

  • Confidence intervals in group sequential trials with random group sizes and applications to survival analysis BIOMETRIKA Lai, T. L., Li, W. 2006; 93 (3): 641-654
  • Efficient recursive estimation and adaptive control in stochastic regression and ARMAX models STATISTICA SINICA Lai, T. L., Ying, Z. 2006; 16 (3): 741-772
  • Modified Haybittle-Peto group sequential designs for testing superiority and non-inferiority hypotheses in clinical trials STATISTICS IN MEDICINE Lai, T. L., Shih, M. C., Zhu, G. R. 2006; 25 (7): 1149-1167

    Abstract

    In designing an active controlled clinical trial, one sometimes has to choose between a superiority objective (to demonstrate that a new treatment is more effective than an active control therapy) and a non-inferiority objective (to demonstrate that it is no worse than the active control within some pre-specified non-inferiority margin). It is often difficult to decide which study objective should be undertaken at the planning stage when one does not have actual data on the comparative advantage of the new treatment. By making use of recent advances in the theory of efficient group sequential tests, we show how this difficulty can be resolved by a flexible group sequential design that can adaptively choose between the superiority and non-inferiority objectives during interim analyses. While maintaining the type I error probability at a pre-specified level, the proposed test is shown to have power advantage and/or sample size saving over fixed sample size tests for either only superiority or non-inferiority, and over other group sequential designs in the literature.

    View details for DOI 10.1002/sim.2357

    View details for Web of Science ID 000236528500005

    View details for PubMedID 16189814

  • A new approach to modeling covariate effects and individualization in population pharmacokinetics-pharmacodynamics JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS Lai, T. L., Shih, M. C., Wong, S. P. 2006; 33 (1): 49-74

    Abstract

    By combining Laplace's approximation and Monte Carlo methods to evaluate multiple integrals, this paper develops a new approach to estimation in nonlinear mixed effects models that are widely used in population pharmacokinetics and pharmacodynamics. Estimation here involves not only estimating the model parameters from Phase I and II studies but also using the fitted model to estimate the concentration versus time curve or the drug effects of a subject who has covariate information but sparse measurements. Because of its computational tractability, the proposed approach can model the covariate effects nonparametrically by using (i) regression splines or neural networks as basis functions and (ii) AIC or BIC for model selection. Its computational and statistical advantages are illustrated in simulation studies and in Phase I trials.

    View details for DOI 10.1007/s10928-005-9000-2

    View details for Web of Science ID 000236842900003

    View details for PubMedID 16402288

  • Maxima of asymptotically Gaussian random fields and moderate deviation approximations to boundary crossing probabilities of sums of random variables with multidimensional indices ANNALS OF PROBABILITY Chan, H. P., Lai, T. L. 2006; 34 (1): 80-121
  • The optimal stopping problem for S-n/n and its ramifications RANDOM WALK, SEQUENTIAL ANALYSIS AND RELATED TOPICS Lai, T. L., Yao, Y. 2006: 131-149
  • Autoregressive models with piecewise constant volatility and regression parameters STATISTICA SINICA Lai, T. L., Liu, H. Y., Xing, H. P. 2005; 15 (2): 279-301
  • Optimal stopping for Brownian motion with applications to sequential analysis and option pricing JOURNAL OF STATISTICAL PLANNING AND INFERENCE Lai, T. L., Lim, T. W. 2005; 130 (1-2): 21-47
  • Power, sample size and adaptation considerations in the design of group sequential clinical trials BIOMETRIKA Lai, T. L., Shih, M. C. 2004; 91 (3): 507-528
  • Self-normalized processes: Exponential inequalities, moment bounds and iterated logarithm laws ANNALS OF PROBABILITY De La Pena, V. H., Klass, M. J., Lai, T. L. 2004; 32 (3A): 1902-1933
  • Exercise regions and efficient valuation of American lookback options MATHEMATICAL FINANCE Lai, T. L., Lim, T. W. 2004; 14 (2): 249-269
  • Valuation of American options via basis functions IEEE TRANSACTIONS ON AUTOMATIC CONTROL Lai, T. L., Wong, S. P. 2004; 49 (3): 374-385
  • Limit theorems for moving averages PROBABILITY, FINANCE AND INSURANCE Lai, T. L. 2004: 1-14
  • A hybrid estimator in nonlinear and generalised linear mixed effects models BIOMETRIKA Lai, T. L., Shih, M. C. 2003; 90 (4): 859-879
  • Saddlepoint approximations and nonlinear boundary crossing probabilities of Markov random walks ANNALS OF APPLIED PROBABILITY Chan, H. P., Lai, T. L. 2003; 13 (2): 395-429
  • Nonparametric estimation in nonlinear mixed effects models BIOMETRIKA Lai, T. L., Shih, M. C. 2003; 90 (1): 1-13
  • Optimal learning and experimentation in bandit problems JOURNAL OF ECONOMIC DYNAMICS & CONTROL Brezzi, M., Lai, T. L. 2002; 27 (1): 87-108
  • Detection and estimation in stochastic systems with time-varying parameters STOCHASTIC THEORY AND CONTROL, PROCEEDINGS Lai, T. L. 2002; 280: 251-265
  • One-sided tests in clinical trials with multiple endpoints BIOMETRICS Bloch, D. A., Lai, T. L., Tubert-Bitter, P. 2001; 57 (4): 1039-1047

    Abstract

    Treatment comparisons in clinical trials often involve several endpoints. For example, one might wish to demonstrate that a new treatment is superior to the current standard for some components of the multivariate response vector and is not inferior, modulo biologically unimportant difference to the standard treatment for all other components. We introduce a new approach to multiple-endpoint testing that incorporates the essential univariate and multivariate features of the treatment effects. This approach is compared with existing methods in a simulation study and applied to data on rheumatoid arthritis patients receiving one of two treatments.

    View details for Web of Science ID 000174956800006

    View details for PubMedID 11764242

  • Asymptotic expansions in multidimensional Markov renewal theory and first passage times for Markov random walks ADVANCES IN APPLIED PROBABILITY Fuh, C. D., Lai, T. L. 2001; 33 (3): 652-673
  • Sequential analysis: Some classical problems and new challenges STATISTICA SINICA Lai, T. L. 2001; 11 (2): 303-351
  • Asymptotic approximations for error probabilities of sequential or fixed sample size tests in exponential families ANNALS OF STATISTICS Chan, H. P., Lai, T. L. 2000; 28 (6): 1638-1669
  • Incomplete learning from endogenous data in dynamic allocation ECONOMETRICA Brezzi, M., Lai, T. L. 2000; 68 (6): 1511-1516
  • Efficient score estimation and adaptive M-estimators in censored and truncated regression models STATISTICA SINICA Kim, C. K., Lai, T. L. 2000; 10 (3): 731-749
  • Sequential multiple hypothesis testing and efficient fault detection-isolation in stochastic systems IEEE TRANSACTIONS ON INFORMATION THEORY Lai, T. L. 2000; 46 (2): 595-608
  • Hybrid resampling methods for confidence intervals STATISTICA SINICA Chuang, C. S., Lai, T. L. 2000; 10 (1): 1-33
  • Moment bounds for self-normalized martingales HIGH DIMENSIONAL PROBABILITY II de la Pena, V. H., Klass, M. J., Lai, T. L. 2000; 47: 3-11
  • Efficient recursive algorithms for detection of abrupt changes in signals and control systems IEEE TRANSACTIONS ON AUTOMATIC CONTROL Lai, T. L., Shan, J. Z. 1999; 44 (5): 952-966
  • Regression smoothers and additive models for censored and truncated data COMMUNICATIONS IN STATISTICS-THEORY AND METHODS Kim, C. K., Lai, T. L. 1999; 28 (11): 2717-2747
  • Information bounds and quick detection of parameter changes in stochastic systems IEEE TRANSACTIONS ON INFORMATION THEORY Lai, T. L. 1998; 44 (7): 2917-2929
  • Wald's equations, first passage times and moments of ladder variables in Markov random walks JOURNAL OF APPLIED PROBABILITY Fuh, C. D., Lai, T. L. 1998; 35 (3): 566-580
  • Resampling methods for confidence intervals in group sequential trials BIOMETRIKA Chuang, C. S., Lai, T. L. 1998; 85 (2): 317-332
  • Repeated significance testing with censored rank statistics in interim analysis of clinical trials STATISTICA SINICA Gu, M. G., Lai, T. L. 1998; 8 (2): 411-428
  • Stochastic adaptive control of linear time-varying systems using auxiliary variables PROCEEDINGS OF THE 37TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-4 Lai, T. L., Li, Z. 1998: 3445-3450
  • Moments of randomly stopped U-STATISTICS ANNALS OF PROBABILITY de la Pena, V. H., Lai, T. L. 1997; 25 (4): 2055-2081
  • Information and prediction criteria for model selection in stochastic regression and ARMA models STATISTICA SINICA Lai, T. L., Lee, C. P. 1997; 7 (2): 285-309
  • Wald's equation and asymptotic bias of randomly stopped U-statistics PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY DELAPENA, V. H., Lai, T. L. 1997; 125 (3): 917-925
  • On optimal stopping problems in sequential hypothesis testing STATISTICA SINICA Lai, T. L. 1997; 7 (1): 33-51
  • Nonparametric estimation and regression analysis with left-truncated and right-censored data JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION Gross, S. T., Lai, T. L. 1996; 91 (435): 1166-1180
  • Bootstrap methods for truncated and censored data STATISTICA SINICA Gross, S. T., Lai, T. L. 1996; 6 (3): 509-530
  • Convergence rate in the strong law of large numbers for Markov chains CONVERGENCE IN ERGODIC THEORY AND PROBABILITY Fuh, C. D., Lai, T. L. 1996; 5: 185-192
  • Computer-based screening of patients with HIV/AIDS for clinical-trial eligibility. The Online journal of current clinical trials Carlson, R. W., Tu, S. W., Lane, N. M., Lai, T. L., Kemper, C. A., Musen, M. A., Shortliffe, E. H. 1995; Doc No 179: [3347 words, 32 paragraphs]

    Abstract

    To assess the potential effect of a computer-based system on accrual to clinical trials, we have developed methodology to identify retrospectively and prospectively patients who are eligible or potentially eligible for protocols.Retrospective chart abstraction with computer screening of data for potential protocol eligibility.A county-operated clinic serving human immunodeficiency virus (HIV) positive patients with or without acquired immune deficiency syndrome (AIDS).A randomly selected group of 60 patients who were HIV-infected, 30 of whom had an AIDS-defining diagnosis.Using a computer-based eligibility screening system, for each clinic visit and hospitalization, patients were categorized as eligible, potentially eligible, or ineligible for each of the 17 protocols active during the 7-month study period. Reasons for ineligibility were categorized.None of the patients was enrolled on a clinical trial during the 7-month period. Thirteen patients were identified as eligible for protocol; three patients were eligible for two different protocols; and one patient was eligible for the same protocol during two different time intervals. Fifty-four patients were identified as potentially eligible for a total of 165 accrual opportunities, but important information, such as the result of a required laboratory test, was missing, so that eligibility could not be determined unequivocally. Ineligibility for protocol was determined in 414 (35%) potential opportunities based only on conditions that were amenable to modification, such as the use of concurrent medications; 194 (17%) failed only laboratory tests or subjective determinations not routinely performed; and 346 (29%) failed only routine laboratory tests.There are substantial numbers of eligible and potentially eligible patients who are not enrolled or evaluated for enrollment in prospective clinical trials. Computer-based eligibility screening when coupled with a computer-based medical record offers the potential to identify patients eligible or potentially eligible for clinical trial, to assist in the selection of protocol eligibility criteria, and to make accrual estimates.

    View details for PubMedID 7719564

  • ASYMPTOTIC NORMALITY OF A CLASS OF ADAPTIVE STATISTICS WITH APPLICATIONS TO SYNTHETIC DATA METHODS FOR CENSORED REGRESSION JOURNAL OF MULTIVARIATE ANALYSIS Lai, T. L., Ying, Z. L., Zheng, Z. K. 1995; 52 (2): 259-279
  • SEQUENTIAL CHANGEPOINT DETECTION IN QUALITY-CONTROL AND DYNAMICAL-SYSTEMS JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-METHODOLOGICAL Lai, T. L. 1995; 57 (4): 613-658
  • ASYMPTOTIC PROPERTIES OF NONLINEAR LEAST-SQUARES ESTIMATES IN STOCHASTIC REGRESSION-MODELS ANNALS OF STATISTICS Lai, T. L. 1994; 22 (4): 1917-1930
  • STATISTICAL-ANALYSIS OF LIGAND-BINDING EXPERIMENTS BIOMETRICS Lai, T. L., Zhang, L. M. 1994; 50 (3): 782-797

    Abstract

    After a brief review of commonly used methods for parameter estimation from ligand-binding data in the biochemistry literature, we propose some diagnostic checks and statistical tests of the underlying assumptions and develop methods for evaluating the biases and variances of the estimates and for constructing confidence intervals. Examples on the analysis of data from two radioligand-binding experiments are presented to illustrate these methods.

    View details for Web of Science ID A1994PL74800017

    View details for PubMedID 7981398

  • A MISSING INFORMATION PRINCIPLE AND M-ESTIMATORS IN REGRESSION-ANALYSIS WITH CENSORED AND TRUNCATED DATA ANNALS OF STATISTICS Lai, T. L., Ying, Z. L. 1994; 22 (3): 1222-1255
  • Nearly optimal generalized sequential likelihood ratio tests in multivariate exponential families MULTIVARIATE ANALYSIS AND ITS APPLICATIONS Lai, T. L., Zhang, L. M. 1994; 24: 331-346
  • EDGEWORTH EXPANSIONS FOR SYMMETRICAL STATISTICS WITH APPLICATIONS TO BOOTSTRAP METHODS STATISTICA SINICA Lai, T. L., WANG, J. Q. 1993; 3 (2): 517-542
  • ASYMPTOTIC THEORY OF A BIAS-CORRECTED LEAST-SQUARES ESTIMATOR IN TRUNCATED REGRESSION STATISTICA SINICA Lai, T. L., Ying, Z. 1992; 2 (2): 519-539
  • BOOTSTRAP CONFIDENCE BANDS FOR SPECTRA AND CROSS-SPECTRA IEEE TRANSACTIONS ON SIGNAL PROCESSING Politis, D. N., Romano, J. P., Lai, T. L. 1992; 40 (5): 1206-1215
  • ASYMPTOTICALLY EFFICIENT ESTIMATION IN CENSORED AND TRUNCATED REGRESSION-MODELS STATISTICA SINICA Lai, T. L., Ying, Z. L. 1992; 2 (1): 17-46
  • CERTAINTY EQUIVALENCE WITH UNCERTAINTY ADJUSTMENTS IN STOCHASTIC ADAPTIVE-CONTROL LECTURE NOTES IN CONTROL AND INFORMATION SCIENCES Lai, T. L. 1992; 184: 270-284
  • RECURSIVE-IDENTIFICATION AND ADAPTIVE PREDICTION IN LINEAR STOCHASTIC-SYSTEMS SIAM JOURNAL ON CONTROL AND OPTIMIZATION Lai, T. L., Ying, Z. L. 1991; 29 (5): 1061-1090
  • LARGE SAMPLE THEORY OF A MODIFIED BUCKLEY-JAMES ESTIMATOR FOR REGRESSION-ANALYSIS WITH CENSORED-DATA ANNALS OF STATISTICS Lai, T. L., Ying, Z. L. 1991; 19 (3): 1370-1402
  • PARALLEL RECURSIVE ALGORITHMS IN ASYMPTOTICALLY EFFICIENT ADAPTIVE-CONTROL OF LINEAR STOCHASTIC-SYSTEMS SIAM JOURNAL ON CONTROL AND OPTIMIZATION Lai, T. L., Ying, Z. L. 1991; 29 (5): 1091-1127
  • ADAPTIVE PREDICTION IN NONLINEAR AUTOREGRESSIVE MODELS AND CONTROL-SYSTEMS STATISTICA SINICA Lai, T. L., Zhu, G. G. 1991; 1 (2): 309-334
  • RANK REGRESSION METHODS FOR LEFT-TRUNCATED AND RIGHT-CENSORED DATA ANNALS OF STATISTICS Lai, T. L., Ying, Z. L. 1991; 19 (2): 531-556
  • ESTIMATING A DISTRIBUTION FUNCTION WITH TRUNCATED AND CENSORED-DATA ANNALS OF STATISTICS Lai, T. L., Ying, Z. L. 1991; 19 (1): 417-442
  • INFORMATION BOUNDS, CERTAINTY EQUIVALENCE AND LEARNING IN ASYMPTOTICALLY EFFICIENT ADAPTIVE-CONTROL OF TIME-INVARIANT STOCHASTIC-SYSTEMS LECTURE NOTES IN CONTROL AND INFORMATION SCIENCES Lai, T. L. 1991; 161: 335-368
  • FUNCTIONAL LAWS OF THE ITERATED LOGARITHM FOR THE PRODUCT-LIMIT ESTIMATOR OF A DISTRIBUTION FUNCTION UNDER RANDOM CENSORSHIP OR TRUNCATION ANNALS OF PROBABILITY Gu, M. G., Lai, T. L. 1990; 18 (1): 160-189
  • STOCHASTIC INTEGRALS OF EMPIRICAL-TYPE PROCESSES WITH APPLICATIONS TO CENSORED REGRESSION JOURNAL OF MULTIVARIATE ANALYSIS Lai, T. L., Ying, Z. L. 1988; 27 (2): 334-358
  • OPEN BANDIT PROCESSES AND OPTIMAL SCHEDULING OF QUEUING-NETWORKS ADVANCES IN APPLIED PROBABILITY Lai, T. L., Ying, Z. L. 1988; 20 (2): 447-472
  • NEARLY OPTIMAL SEQUENTIAL-TESTS OF COMPOSITE HYPOTHESES ANNALS OF STATISTICS Lai, T. L. 1988; 16 (2): 856-886
  • BOUNDARY CROSSING PROBLEMS FOR SAMPLE MEANS ANNALS OF PROBABILITY Lai, T. L. 1988; 16 (1): 375-396
  • FIXED ACCURACY ESTIMATION OF AN AUTOREGRESSIVE PARAMETER ANNALS OF STATISTICS Lai, T. L., Siegmund, D. 1983; 11 (2): 478-485
  • SEQUENTIAL MEDICAL TRIALS PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-PHYSICAL SCIENCES Lai, T. L., Levin, B., Robbins, H., Siegmund, D. 1980; 77 (6): 3135-3138

    Abstract

    A model for sequential clinical trials is discussed. Three proposed stopping rules are studied by the Monte Carlo method for small patient horizons and mathematically for large patient horizons. They are shown to be about equally effective and asymptotically optimal from both Bayesian and frequentist points of view and are markedly superior to any fixed sample size procedure.

    View details for Web of Science ID A1980JY17300016

    View details for PubMedID 16592839

  • NON-LINEAR RENEWAL THEORY WITH APPLICATIONS TO SEQUENTIAL-ANALYSIS .2. ANNALS OF STATISTICS Lai, T. L., Siegmund, D. 1979; 7 (1): 60-76
  • NONLINEAR RENEWAL THEORY WITH APPLICATIONS TO SEQUENTIAL-ANALYSIS I ANNALS OF STATISTICS Lai, T. L., Siegmund, D. 1977; 5 (5): 946-954

Stanford Medicine Resources: