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A Handbook of Statistical Analyses using SAS

Sofort lieferbar | Lieferzeit: Sofort lieferbar I
ISBN-13:
9781584887850
Veröffentl:
2008
Seiten:
392
Autor:
Geoff Der
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
0 - No protection
Sprache:
Englisch
Beschreibung:

Remaining the go-to resource for learning how to use SAS for many kinds of statistical analysis, this third edition of a bestseller explains how to conduct a range of statistical analyses using the latest version of SAS. It illustrates each type of analysis with numerous real-world data examples, such as environmental causes of diseases, hypertension treatment, and gastric cancer treatment. This edition presents the new graphics procedures of SAS 9.2. It also includes more end-of-chapter exercises and selected answers in the appendix, along with a solutions manual that provides SAS code, output, and comments. The SAS programs and data sets used in the book are available online.
Introduction to SAS. Data Description and Simple Inference: Mortality and Water Hardness in the United Kingdom. Simple Inference for Categorical Data: From Sandflies to Organic Particulates in the Air. Analysis of Variance I: Treating Hypertension. Analysis of Variance II: School Attendance among Australian Children. Simple Linear Regression: Alcohol Consumption and Cirrhosis Deaths and How Old Is the Universe? Multiple Regression: Determinants of the Crime Rate in States of the United States. Logistic Regression: Psychiatry Screening, Plasma Proteins, Danish Do-It-Yourself, and Lower Back Pain. Generalized Linear Models: Polyposis and School Attendance among Australian School Children. Generalized Additive Models: Burning Rubber and Air Pollution in the United States. Analysis of Variance of Repeated Measures Visual Acuity. Longitudinal Data I: Treatment of Postnatal Depression. Longitudinal Data II: Linear Mixed Models. Longitudinal Data III: Generalized Estimating Equations and Generalized Mixed Models. Survival Analysis: Gastric Cancer, the Treatment of Heroin Addicts, and Heart Transplants. Principal Components Analysis and Factor Analysis: Olympic Decathlon and Statements about Pain. Cluster Analysis: Air Pollution in the United States. Discriminant Function Analysis: Classifying Tibetan Skulls. Correspondence Analysis: Smoking and Motherhood, Sex and the Single Girl, and European Stereotypes. Appendix. References. Index.

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