Thomas J. Santner

Bio: Thomas J. Santner is an academic researcher from Ohio State University. The author has contributed to research in topics: Computer experiment & Estimator. The author has an hindex of 29, co-authored 109 publications receiving 9567 citations. Previous affiliations of Thomas J. Santner include Cornell University & Hospital for Special Surgery.

The design and analysis of computer experiments

Abstract: Many scientific phenomena are now investigated by complex computer models or codes A computer experiment is a number of runs of the code with various inputs A feature of many computer experiments is that the output is deterministic--rerunning the code with the same inputs gives identical observations Often, the codes are computationally expensive to run, and a common objective of an experiment is to fit a cheaper predictor of the output to the data Our approach is to model the deterministic output as the realization of a stochastic process, thereby providing a statistical basis for designing experiments (choosing the inputs) for efficient prediction With this model, estimates of uncertainty of predictions are also available Recent work in this area is reviewed, a number of applications are discussed, and we demonstrate our methodology with an example

The Statistical Analysis of Discrete Data

Abstract: 1 Introduction.- 2 Univariate Discrete Responses.- 3 Loglinear Models.- 4 Cross-Classified Data.- 5 Univariate Discrete Data with Covariates.- Appendix 1. Some Results from Linear Algebra.- Appendix 2. Maximization of Concave Functions.- Appendix 3. Proof of Proposition 3.3.1 (ii) and (iii).- Appendix 4. Elements of Large Sample Theory.- Problems.- References.- List of Notation.- Index to Data Sets.- Author Index.

Changes in the moment arms of the rotator cuff and deltoid muscles with abduction and rotation

Abstract: The behavior of the moment arms of the rotator cuff and deltoid muscles was studied during simple and combine movements of abduction and rotation about the glenohumeral joint. This was done by experimental measurement of excursions of the muscles in an in vitro cadaver model and by use of a multiple-regression analysis to delineate the changes in the moment arms as a function of abduction and rotation. The results demonstrated the potential of some rotator cuff muscles to contribute to both abduction and rotation, the sensitivity of the abductor moment-arm lengths to internal and external rotation and of the rotator moment-arm lengths to the degree of abduction, and the capacity of the abductor moment-arm lengths of the deltoid to increase with increasing abduction. Characterization of this behavior resulted in an increased understanding of the complex role of the rotator cuff and deltoid muscles about the gleno-humeral joint and provided quantitative descriptions of functional relationships. This study demonstrates the capacity of the infraspinatus and subscapularis muscles to contribute not only to external and internal rotation, respectively, but also to elevation of the arm in the plane of the scapula, a role for which these muscles have been given little or no consideration. Furthermore, it demonstrates that the contribution of the infraspinatus to abduction is enhanced with internal rotation while that of the subscapularis is enhanced with external rotation. Thus, dysfunction of the supraspinatus muscle need not preclude good elevation of the arm, and rehabilitation to reprogram and strengthen the remaining muscles becomes an important consideration.

Arthrodesis as an early alternative to nonoperative management of charcot arthropathy of the diabetic foot.

Abstract: Background: This study was performed to evaluate the use of arthrodesis of the tarsal-metatarsal area for the treatment of Eichenholtz stage-I Charcot arthropathy in patients with diabetes. Currently, the standard treatment of stage-I Charcot arthropathy is the application of a non-weight-bearing total-contact cast. Although this treatment can be effective for allowing a patient to walk without undergoing an operation, a nonunion or malunion may still result. The subsequent deformities may lead to complications, including ulceration of the foot and the need for operative intervention. Recently, a group of patients who had had early operative intervention for a variety of reasons provided us with the opportunity to objectively evaluate the effects of such treatment. This analysis provided valuable information about whether this treatment is a reasonable alternative to current nonoperative approaches. Methods: Between January 1991 and December 1996, fourteen patients had an operation because of Eichenholtz stage-I diabetic neuropathy. The classification of the disease as Eichenholtz stage I (the developmental stage) was based on radiographic evidence of varying degrees of articular-surface and subchondral-bone resorption and fragmentation as well as joint subluxation or dislocation without evidence of coalescence or callus formation. The operative procedure consisted of extensive debridement, open reduction, and internal fixation of the tarsal-metatarsal region with autologous bone graft. Postoperative treatment consisted of immobilization of the limb in a non-weight-bearing cast for a minimum of six weeks. All of the patients returned for a final follow-up visit at a mean of forty-one months (range, 25.3 to 77.3 months) postoperatively, at which time clinical and radiographic evaluations as well as gait analysis (with measurement of plantar pressures) were performed. The gait-analysis data was compared with similar data from a group of fourteen patients with diabetic neuropathy who had had a below-the-knee amputation and with that from a group of fourteen patients with diabetic neuropathy who had no history of plantar ulceration. Results: All of the arthrodesis procedures were successful. Clinically, none of the patients had immediate or long-term complications postoperatively. No patient reported ulceration after the operation. The mean time to assisted weight-bearing was 10 ± 3.3 weeks (range, six to fifteen weeks), the mean time to unassisted weight-bearing was 15 ±8.8 weeks (range, eight to thirty-four weeks), and the mean time to return to the use of regular shoes was 27 ±14.4 weeks (range, twelve to sixty weeks). All of the patients regained the level of walking ability that they had had prior to the arthropathy. The calculated confidence intervals revealed no differences between the arthrodesis group and either of the two comparison groups with regard to the time-distance gait parameters of velocity, cadence, and stride length or with regard to the minimum, maximum, and total range of motion of each of the joints. In contrast to able-bodied subjects, all three groups showed a reduction in sagittal-plane ankle motion that was primarily related to loss of plantar flexion. The first metatarsal, great toe, and heel showed the highest peak plantar pressures, with little difference among the groups. Conclusions: To our knowledge, the present study is the first to demonstrate the potential for early operative treatment to restore anatomical alignment and improve function of diabetic patients with stage-I Charcot arthropathy.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Gaussian Processes for Machine Learning

Abstract: A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.

An introduction to categorical data analysis

Abstract: Two--Way Contingency Tables. Three--Way Contingency Tables. Generalized Linear Models. Logistic Regression. Loglinear Models for Contingency Tables. Building and Applying Logit and Loglinear Models. Multicategory Logit Models. Models for Matched Pairs. A Twentieth--Century Tour of Categorical Data Analysis. Appendix. Table of Chi--Squared Distribution Values for Various Right--Tail Probabilities. Bibliography. Indexes.

The design and analysis of computer experiments

Abstract: Many scientific phenomena are now investigated by complex computer models or codes A computer experiment is a number of runs of the code with various inputs A feature of many computer experiments is that the output is deterministic--rerunning the code with the same inputs gives identical observations Often, the codes are computationally expensive to run, and a common objective of an experiment is to fit a cheaper predictor of the output to the data Our approach is to model the deterministic output as the realization of a stochastic process, thereby providing a statistical basis for designing experiments (choosing the inputs) for efficient prediction With this model, estimates of uncertainty of predictions are also available Recent work in this area is reviewed, a number of applications are discussed, and we demonstrate our methodology with an example