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An abundance of real-world examples highlights this step-by-step guide to producing tables and reports using the TABULATE procedure. Beginning and intermediate SAS users will find that the format is both convenient and inviting. Applications are presented in a self-contained, two-page layout; discussion material and sample code are on one page, and the resulting tables are on the facing page. Topics are presented in order of increasing complexity, making this an excellent training manual or self-tutorial. The concise format also makes this a quick reference guide for specific applications for more advanced users. A very handy section on common problems and their solutions is also included. With this book, you will quickly learn how to generate tables using macros, create tables using SAS/ASSIST software, present output on the Internet, handle percentages and missing data, modify row and column headings, and produce one-, two-, and three-dimensional tables using PROC TABULATE. Also provided are more advanced tips on complex formatting and exporting PROC TABULATE to other applications.

QA 276.4 Mathematical statistics. Data processing --- QA 276.4 Mathematical statistics. Data processing --- QA 276.4 Mathematical statistics. Data processing --- Statistics Tables --- Statistics Tables --- Automatic Data Processing --- Automatic Data Processing --- Automatic Data Processing

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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.

QA 76.9 D345 Data preparation --- Automatic Data Processing --- Automatic Data Processing --- Automatic Data Processing --- SAS --- SAS --- SAS --- Programming Languages --- Programming Languages --- Programming Languages

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Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with this fully updated new edition that incorporates the many enhancements in SAS procedures for survival analysis in SAS 9. Although the book assumes only a minimal knowledge of SAS, more experienced users will learn new techniques of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book, ensuring that even the uninitiated become sophisticated users 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 in survival analysis books, such as time-dependent covariates, competing risks, and repeated events. Survival Analysis Using SAS: A Practical Guide, Second Edition, has been thoroughly updated for SAS 9, and all figures are presented using ODS Graphics. This new edition also documents major enhancements to the STRATA statement in the LIFETEST procedure; includes a section on the PROBPLOT command, which offers graphical methods to evaluate the fit of each parametric regression model; introduces the new BAYES statement for both parametric and Cox models, which allows the user to do a Bayesian analysis using MCMC methods; demonstrates the use of the counting process syntax as an alternative method for handling time-dependent covariates; contains a section on cumulative incidence functions; and describes the use of the new GLIMMIX procedure to estimate random-effects models for discrete-time data.

Failure time data analysis --- Survival analysis (Biometry) --- Survival Analysis --- Automatic Data Processing --- Data processing --- SAS (Computer file) --- Analyse de survie (biométrie) --- SAS (logiciel) --- Temps entre défaillances, Analyse des --- Statistique médicale --- Informatique --- QA 76.755 - Computer Software. Handbook --- SAS --- Handbooks --- Software --- Electronic data processing --- Statistique médicale. --- Informatique. --- Failure time data analysis - Data processing --- Survival analysis (Biometry) - Data processing

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At last! A comprehensive, applications-oriented mixed models guide for data analysis. Discover the latest capabilities available for a wide range of applications featuring the MIXED procedure in SAS/STAT software. This practical guide integrates the theory underlying the models, the specific forms of the models for various applications, and examples from many different fields of study using appropriate SAS code with interpretation of results. Specific models discussed include: simple random-effect only, simple mixed with a single fixed and random effect, split-plot, multilocation, repeated measures, analysis of covariance, random coefficients, and spatial correlation. With a background in two-way ANOVA and regression and basic knowledge of linear models and matrix algebra, you will benefit from the discussion of basic to advanced topics in this book. A working knowledge of experimental design is also helpful.

Biomathematics. Biometry. Biostatistics --- Programming --- Mathematical statistics --- Data processing. --- SAS (Computer file) --- SAS (Computer file). --- Méthode statistique --- Expérimentation --- experimentation --- Échantillonnage --- Sampling --- Data processing --- Statistical analysis system --- SAS system --- Statistical methods --- design --- experimentation. --- Mathematical statistics - Data processing. --- QA 76.755 - Computer Software. Handbook --- SAS

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HD 30.2 Electronic Data Processing. Information Technology. Artificial Intelligence. Knowledge Management --- HD 30.2 Electronic Data Processing. Information Technology. Artificial Intelligence. Knowledge Management --- HD 30.2 Electronic Data Processing. Information Technology. Artificial Intelligence. Knowledge Management --- Knowledge management --- Knowledge management --- Knowledge management --- Communities of practice --- Communities of practice --- Communities of practice