SAS/STAT 9. 3 User's Guide PDF Download
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Author: Sas Institute
Publisher:
ISBN: 9781607646341
Category :
Languages : en
Pages : 0
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Book Description
The GLIMMIX procedure fits and analyzes generalized linear mixed models (GLMM), models with random effects for data that can be nonnormally distributed. This title is also available online.
Author: Sas Institute
Publisher:
ISBN: 9781607646341
Category :
Languages : en
Pages : 0
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Book Description
The GLIMMIX procedure fits and analyzes generalized linear mixed models (GLMM), models with random effects for data that can be nonnormally distributed. This title is also available online.
Author: Rudolf Freund
Publisher: John Wiley & Sons
ISBN: 0471416649
Category : Mathematics
Languages : en
Pages : 258
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Book Description
SAS® System for Regression Learn to perform a wide variety of regression analyses using SAS® software with this example-driven revised favorite from SAS Publishing. With this Third Edition you will learn the basics of performing regression analyses using a wide variety of models including nonlinear models. Other topics covered include performing linear regression analyses using PROC REG diagnosing and providing remedies for data problems, including outliers and multicollinearity. Examples feature numerous SAS procedures including REG, PLOT, GPLOT, NLIN, RSREG, AUTOREG, PRINCOMP, and others. A helpful discussion of theory is supplied where necessary. Some knowledge of both regression and the SAS System are assumed. New for this edition The Third Edition includes revisions, updated material, and new material. You’ll find new information on using SAS/INSIGHT® software regression with a binary response with emphasis on PROC LOGISTIC nonparametric regression (smoothing) using moving averages and PROC LOESS. Additionally, updated material throughout the book includes high-resolution PROC REG graphics output, using the OUTEST option to produce a data set, and using PROC SCORE to predict another data set.
Author: Paul D. Allison
Publisher: SAS Institute
ISBN: 1629590185
Category : Computers
Languages : en
Pages : 348
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Book Description
Informal and nontechnical, this book both explains the theory behind logistic regression, and looks at all the practical details involved in its implementation using SAS. Includes several real-world examples in full detail.
Author: Naeem Siddiqi
Publisher: John Wiley & Sons
ISBN: 1119279151
Category : Business & Economics
Languages : en
Pages : 469
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Book Description
A better development and implementation framework for credit risk scorecards Intelligent Credit Scoring presents a business-oriented process for the development and implementation of risk prediction scorecards. The credit scorecard is a powerful tool for measuring the risk of individual borrowers, gauging overall risk exposure and developing analytically driven, risk-adjusted strategies for existing customers. In the past 10 years, hundreds of banks worldwide have brought the process of developing credit scoring models in-house, while ‘credit scores' have become a frequent topic of conversation in many countries where bureau scores are used broadly. In the United States, the ‘FICO' and ‘Vantage' scores continue to be discussed by borrowers hoping to get a better deal from the banks. While knowledge of the statistical processes around building credit scorecards is common, the business context and intelligence that allows you to build better, more robust, and ultimately more intelligent, scorecards is not. As the follow-up to Credit Risk Scorecards, this updated second edition includes new detailed examples, new real-world stories, new diagrams, deeper discussion on topics including WOE curves, the latest trends that expand scorecard functionality and new in-depth analyses in every chapter. Expanded coverage includes new chapters on defining infrastructure for in-house credit scoring, validation, governance, and Big Data. Black box scorecard development by isolated teams has resulted in statistically valid, but operationally unacceptable models at times. This book shows you how various personas in a financial institution can work together to create more intelligent scorecards, to avoid disasters, and facilitate better decision making. Key items discussed include: Following a clear step by step framework for development, implementation, and beyond Lots of real life tips and hints on how to detect and fix data issues How to realise bigger ROI from credit scoring using internal resources Explore new trends and advances to get more out of the scorecard Credit scoring is now a very common tool used by banks, Telcos, and others around the world for loan origination, decisioning, credit limit management, collections management, cross selling, and many other decisions. Intelligent Credit Scoring helps you organise resources, streamline processes, and build more intelligent scorecards that will help achieve better results.
Author: Scott Menard
Publisher: SAGE
ISBN: 9780761922087
Category : Mathematics
Languages : en
Pages : 130
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Book Description
The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included. More detailed consideration of grouped as opposed to case-wise data throughout the book Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data Updated coverage of unordered and ordered polytomous logistic regression models.
Author: Joseph M. Hilbe
Publisher: CRC Press
ISBN: 1498709583
Category : Mathematics
Languages : en
Pages : 170
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Book Description
Practical Guide to Logistic Regression covers the key points of the basic logistic regression model and illustrates how to use it properly to model a binary response variable. This powerful methodology can be used to analyze data from various fields, including medical and health outcomes research, business analytics and data science, ecology, fishe
Author: David W. Hosmer, Jr.
Publisher: Wiley-Interscience
ISBN: 9780471225898
Category : Mathematics
Languages : en
Pages : 0
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Book Description
From the reviews of the First Edition. "An interesting, useful, and well-written book on logistic regression models. . . Hosmer and Lemeshow have used very little mathematics, have presented difficult concepts heuristically and through illustrative examples, and have included references.
Author: Ann A. O'Connell
Publisher: SAGE
ISBN: 9780761929895
Category : Mathematics
Languages : en
Pages : 124
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Book Description
Ordinal measures provide a simple and convenient way to distinguish among possible outcomes. The book provides practical guidance on using ordinal outcome models.
Author: Paul D. Allison
Publisher: Wiley-SAS
ISBN: 9780471221753
Category : Mathematics
Languages : en
Pages : 308
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Book Description
Written in an informal and non-technical style, this book first explains the theory behind logistic regression and then shows how to implement it using the SAS System. Allison includes several detailed, real-world examples of the social sciences to provide readers with a better understanding of the material. He also explores the differences and similarities among the many generalizations of the logistic regression model.
Author: Geoff Der
Publisher: CRC Press
ISBN: 1439867984
Category : Mathematics
Languages : en
Pages : 539
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Book Description
Written with medical statisticians and medical researchers in mind, this intermediate-level reference explores the use of SAS for analyzing medical data. Applied Medical Statistics Using SAS covers the whole range of modern statistical methods used in the analysis of medical data, including regression, analysis of variance and covariance, longitudi
