Typescript (photocopy). / Digitized by Kansas Correctional Industries

Lee Shun-yi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 57-61). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Tests of Hypotheses --- p.4 / Chapter 1.2.1 --- Likelihood Ratio Statistic --- p.4 / Chapter 1.2.2 --- The Rao´ة s Score Statistic --- p.5 / Chapter 1.2.3 --- Wald's Statistic --- p.6 / Chapter 1.3 --- Notation --- p.6 / Chapter 2 --- Fixed Effects Model --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- Pearson Chi-square Statistic --- p.9 / Chapter 2.3 --- Logistic Regression Model --- p.11 / Chapter 2.3.1 --- Testing Linear Hypotheses about the Regression Coefficients --- p.12 / Chapter 2.4 --- Combining Proportions --- p.16 / Chapter 2.4.1 --- Classical Estimators --- p.17 / Chapter 2.4.2 --- Jackknife Estimator --- p.18 / Chapter 2.4.3 --- Cross-validatory estimators --- p.19 / Chapter 3 --- Random Effects Model --- p.21 / Chapter 3.1 --- Introduction --- p.21 / Chapter 3.2 --- DerSimonian and Laird Method --- p.22 / Chapter 3.3 --- Generalized linear model with random effect --- p.24 / Chapter 3.3.1 --- Quasi-Likelihood --- p.25 / Chapter 3.3.2 --- Testing Linear Hypotheses about the Regression Coefficients --- p.26 / Chapter 3.3.3 --- MINQUE --- p.27 / Chapter 3.3.4 --- Score Test --- p.31 / Chapter 4 --- Overdispersion and Intraclass Correlation --- p.36 / Chapter 4.1 --- Introduction --- p.36 / Chapter 4.2 --- C(α) Test --- p.39 / Chapter 4.2.1 --- Correlated Binomial model and Beta-Binomial model --- p.40 / Chapter 4.2.2 --- C(α) Statistic Based On Quasi-likclihood --- p.46 / Chapter 4.3 --- Donner Statistic --- p.48 / Chapter 4.4 --- Rao and Scott Statistic --- p.51 / Chapter 5 --- Example and Discussion --- p.53 / Bibliography --- p.57

<div>The simulation optimization problems refer to the nonlinear optimization problems whose objective function can be evaluated through stochastic simulations. We study two significant discrete simulation optimization problems in this thesis: Ranking and Selection (R&S) and Factor Screening (FS). Both R&S and FS are the "selection" problems defined upon a finite set of candidate systems or factors. They vary mainly in their objectives: the R&S problems is to find the "best" system(s) among all alternatives; whereas the FS is to select important factors that are critical to the stochastic systems. </div><div><br></div><div>In this thesis, we develop efficient sequential procedures for these two problems. For the R&S problem, we propose fully-sequential procedures for selecting the "best" systems with a guaranteed probability of correct selection (PCS). The main features of the stated methods are: (1) a Bonferroni-free model, these procedures overcome the conservativeness of the Bonferroni correction and deliver the exact probabilistic guarantee without overshooting; (2) asymptotic optimality, these procedures achieve the lower bound of average sample size asymptotically; (3) an indifference-zone-flexible formulation, these procedures bridge the gap between the indifference-zone formulation and the indifference-zone-free formulation so that the indifference-zone parameter is not indispensable but could be helpful if provided. We establish the validity and asymptotic efficiency for the proposed procedure and conduct numerical studies to investigates the performance under multiple configurations.</div><div><br></div><div>We also consider the multi-objective R&S (MOR&S) problem. To the best of our knowledge, the procedure proposed is the first frequentist approach for MOR&S. These procedures identify the Pareto front with a guaranteed probability of correct selection (PCS). In particular, these procedures are fully sequential using the test statistics built upon the Generalized Sequential Probability Ratio Test (GSPRT). The main features are: 1) an objective-dimension-free model, the performance of these procedures do not deteriorate as the number of objectives increases, and achieve the same efficiency as KN family procedures for single-objective ranking and selection problem; 2) an indifference-zone-flexible formulation, the new methods eliminate the necessity of indifference-zone parameter while makes use of the indifference-zone information if provided. A numerical evaluation demonstrates the validity efficiency of the new procedure.</div><div><br></div><div>For the FS problem, our objective is to identify important factors for simulation experiments with controlled Family-Wise Error Rate. We assume a Multi-Objective first-order linear model where the responses follow a multivariate normal distribution. We offer three fully-sequential procedures: Sum Intersection Procedure (SUMIP), Sort Intersection Procedure (SORTIP), and Mixed Intersection procedure (MIP). SUMIP uses the Bonferroni correction to adjust for multiple comparisons; SORTIP uses the Holms procedure to overcome the conservative of the Bonferroni method, and MIP combines both SUMIP and SORTIP to work efficiently in the parallel computing environment. Numerical studies are provided to demonstrate the validity and efficiency, and a case study is presented.</div>

Thomas Marill. / "October 30, 1956." "This report is based on a thesis submitted to the Department of Economics and Social Science, M.I.T., in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Psychology, June 1956." / Bibliography: p. 73. / Army Signal Corps Contract DA36-039-sc-64637 Dept. of the Army Task No. 3-99-06-108 Project No. 3-99-00-100

No description available.

In this thesis, I examine how auditors construct their mental representations and test their hypotheses about the strength of a client’s control environment. With regard to the former, I hypothesize that management’s frame of the control system and auditor’s retrieval of control environment information from memory may influence the auditor’s control environment mental representation and impact subsequent audit judgments. Consistent with my theoretical predictions, I find that retrieval of control environment information from memory biases an auditor’s mental representation, and that this biased mental representation impacts subsequent fraud assessment. In addition, there is limited evidence to support the conjecture that auditors may be susceptible to management’s framing of the internal control system resulting in relatively positive control environment evaluations which was found to transfer to some subsequent audit judgments. With regard to the latter, prior audit literature has examined how auditors evaluate person specific characteristics, such as competence, of other auditors, however there has been no research that has examined how auditors test such characteristics of client management. I disentangle whether auditors utilize a diagnostic and/or a conservative hypothesis testing strategy when testing client management’s ethicality and competence as these are fundamental components of the client’s control environment. A diagnostic testing strategy is evidenced by the auditor searching for the most informative information, whereas a conservative testing strategy is evidenced by the auditor searching for risks. I examine how a checklist decision aid contained in the current institutional context may inhibit auditors’ utilization of a diagnostic testing strategy, and examine how a schematic decision aid is able to enhance diagnostic testing. The results indicate that auditors utilize both diagnostic and conservative testing strategies when testing client management ethicality; however, the auditor’s testing strategy is only diagnostic when testing client management competence. In regard to decision aids, I found that when testing client management ethicality and competence, a schematic decision aid was able to increase the auditor’s extent of diagnostic testing. The checklist decision aid decreased the auditor’s extent of diagnostic testing only when testing client management ethicality, and was not different from unaided judgments when testing client management competence. / Thesis (Ph.D, Management) -- Queen's University, 2011-02-22 13:43:07.232

Thesis (Ph. D.)--University of California, San Diego, 2005. / Vita. Includes bibliographical references (leaves 215-220).

Thesis--Copenhagen. / Summary in Danish. Bibliography: p. 210-219.

Thesis (Ph. D.)--Florida State University, 2004. / Advisor: Dr. Joseph Pignatiello, Jr., Florida State University, College of Engineering, Dept. of Industrial Engineering. Title and description from dissertation home page (viewed Sept. 23, 2004). Includes bibliographical references.

Thesis (M. Phil.)--University of Hong Kong, 1994.