Professional Development with Visio 2000 empowers you to create your own Visio solutions quickly and easily. Using client-proven methods, and the success of his training seminars worldwide, Visio insider David Edson provides you with an understanding of the Visio development platform, and guides you through the use of Visual Basic for Applications (VBA), enabling you to create your own Visio solutions. You will benefit from David's expert knowledge of topics including understanding Visio solutions, working with SmartShapes, customizing ShapeSheets, Visio VBA automation, Generating Visio Drawings with ActiveX Automation, and much more.

The key to ensuring accurate data is having clean data. This book develops and describes data cleaning programs and macros. You can use many of the programs and macros that are provided, as is, or you can modify them for your own special data cleaning tasks. Ron has carefully explained and documented each of the programs and macros, thus providing you with SAS programming instruction on an intermediate-to-advanced level. Topics presented include validation checks on character data, numeric data, missing values, and date values; searching for duplicate records; working with multiple files; double entry and verification using the COMPARE procedure; and SQL solutions and using validation data sets. Written in Ron's signature informal, tutorial style, this book gives anyone who manages data thoroughly documented, step-by-step instructions for the development of data cleaning programs and macros. Supports releases 6.12 and higher of SAS software.

This issue discusses the six steps involved in defining a client's training needs in relation to the organization's overall business goals. Offers techniques to use at each point in the analysis process plus sample questions used for collecting data.

If you are a researcher or student with experience in multiple linear regression and want to learn about logistic regression, this book is for you! Informal and nontechnical, this book both explains the theory behind logistic regression and looks at all the practical details involved in its implementation using the SAS System. Several social science real-world examples are included in full detail. This book also explains the differences and similarities among the many generalizations of the logistic regression model. The following topics are covered: binary logit analysis, logit analysis of contingency tables, multinomial logit analysis, ordered logit analysis, discrete-choice analysis with the PHREG procedure, and Poisson regression. Other highlights include discussions on how to use the GENMOD procedure to do loglinear analysis and GEE estimation for longitudinal binary data. Only basic knowledge of the SAS DATA step is assumed. Supports releases 6.12 and higher of SAS software.

Real-world problems and data sets are the backbone of Ravindra Khattree and Dayanand Naik's Applied Multivariate Statistics with SAS Software, Second Edition, which provides a unique approach to the topic, integrating statistical methods, data analysis, and applications. Now extensively revised, the book includes new information about mixed effects models, applications of the MIXED procedure, regression diagnostics with the corresponding IML procedure code, and covariance structures. The authors' approach to the information will aid professors, researchers, and students in a variety of disciplines and industries. Extensive SAS code and the corresponding high-resolution output accompany sample problems, and clear explanations of SAS procedures are included. Emphasis is on correct interpretation of the output to draw meaningful conclusions. Featuring both the theoretical and the practical, topics covered include multivariate analysis of experimental data and repeated measures data, graphical representation of data including biplots, and multivariate regression. In addition, a quick introduction to the IML procedure with special reference to multivariate data is available in an appendix. SAS programs and output integrated with the text make it easy to read and follow the examples.

65669-4 The field’s leading text, now completely updated. Modeling dynamical systems — theory, methodology, and applications. Lennart Ljung’s System Identification: Theory for the User is a complete, coherent description of the theory, methodology, and practice of System Identification. This completely revised Second Edition introduces subspace methods, methods that utilize frequency domain data, and general non-linear black box methods, including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples designed for Ljung’s market-leading software, System Identification Toolbox for MATLAB. Ljung combines careful mathematics, a practical understanding of real-world applications, and extensive exercises. He introduces both black-box and tailor-made models of linear as well as non-linear systems, and he describes principles, properties, and algorithms for a variety of identification techniques: Nonparametric time-domain and frequency-domain methods. Parameter estimation methods in a general prediction error setting. Frequency domain data and frequency domain interpretations. Asymptotic analysis of parameter estimates. Linear regressions, iterative search methods, and other ways to compute estimates. Recursive (adaptive) estimation techniques. Ljung also presents detailed coverage of the key issues that can make or break system identification projects, such as defining objectives, designing experiments, controlling the bias distribution of transfer-function estimates, and carefully validating the resulting models. The first edition of System Identification has been the field’s most widely cited reference for over a decade. This new edition will be the new text of choice for anyone concerned with system identification theory and practice.

This issue explains how to analyze work and work processes using methods such as:observation, interviews, checklists, critical incident technique, and process mapping. It provides case studies that illustrate how training practitioners apply the principles of analysis to create training deliverables.

This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH) models and applications. For the first time, Modelling Stock Market Volatility provides new insights about the links between these two models and new work on practical estimation methods for continuous time models. Featuring the pioneering scholarship of Daniel Nelson, the text presents research about the discrete time model, continuous time limits and optimal filtering of ARCH models, and the specification and estimation of continuous time processes. This work will lead to a rapid growth in their empirical application as they are increasingly subjected to routine specification testing. Key Features * Provides for the first time new insights on the links between continuous time and ARCH models * Collects seminal scholarship by some of the most renowned researchers in finance and econometrics * Captures complex arguments underlying the approximation and proper statistical modelling of continuous time volatility dynamics

This book provides solutions to the problems in The SAS Workbook. Use it to compare your own programs to those created by the author of the problems workbook. Alternate solutions are offered for a number of the problems.

This book is part of the SAS Press program.

Learn by doing as you work through the programming problems offered in this unique book! Beginning with problems related to the DATA step, moving to elementary and then advanced exercises on frequently used SAS procedures, and also covering problems in statistical analysis, the book offers challenges for beginning, intermediate, and advanced programmers. Students, teachers, and trainers will be able to work with Base SAS procedures such as FORMAT, PRINT, TABULATE, and PLOT; solve simple descriptive statistics problems as well as those using the FREQ, TTEST, GLM, ANOVA, and NPAR1WAY procedures; and have fun with some SAS brainteasers in the book's last section. Each chapter gives readers a good start on solving the problem by providing directions and hints about useful programming tools. As a service to our educational market, look for The SAS Workbook Solutions sold separately. This book is part of the SAS Press program.

Biomedical and social science researchers who want to analyze survival data with SAS will find just what they need with this easy-to-read and comprehensive guide. Written for the reader with a modest statistical background and minimal knowledge of SAS software, this book teaches many aspects of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical resource, ensuring that even the uninitiated becomes a sophisticated user of survival analysis. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered, such as time-dependent covariates, competing risks, and repeated events.