- 326 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Complex Survey Data Analysis with SAS
About this book
Complex Survey Data Analysis with SAS® is an invaluable resource for applied researchers analyzing data generated from a sample design involving any combination of stratification, clustering, unequal weights, or finite population correction factors. After clearly explaining how the presence of these features can invalidate the assumptions underlying most traditional statistical techniques, this book equips readers with the knowledge to confidently account for them during the estimation and inference process by employing the SURVEY family of SAS/STAT® procedures.
The book offers comprehensive coverage of the most essential topics, including:
- Drawing random samples
- Descriptive statistics for continuous and categorical variables
- Fitting and interpreting linear and logistic regression models
- Survival analysis
- Domain estimation
- Replication variance estimation methods
- Weight adjustment and imputation methods for handling missing data
The easy-to-follow examples are drawn from real-world survey data sets spanning multiple disciplines, all of which can be downloaded for free along with syntax files from the author's website: http://mason.gmu.edu/~tlewis18/.
While other books may touch on some of the same issues and nuances of complex survey data analysis, none features SAS exclusively and as exhaustively. Another unique aspect of this book is its abundance of handy workarounds for certain techniques not yet supported as of SAS Version 9.4, such as the ratio estimator for a total and the bootstrap for variance estimation.
Taylor H. Lewis is a PhD graduate of the Joint Program in Survey Methodology at the University of Maryland, College Park, and an adjunct professor in the George Mason University Department of Statistics. An avid SAS user for 15 years, he is a SAS Certified Advanced programmer and a nationally recognized SAS educator who has produced dozens of papers and workshops illustrating how to efficiently and effectively conduct statistical analyses using SAS.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Table of Contents
- Preface
- Author
- 1. Features and Examples of Complex Surveys
- 2. Drawing Random Samples Using PROC SURVEYSELECT
- 3. Analyzing Continuous Variables Using PROC SURVEYMEANS
- 4. Analyzing Categorical Variables Using PROC SURVEYFREQ
- 5. Fitting Linear Regression Models Using PROC SURVEYREG
- 6. Fitting Logistic Regression Models Using PROC SURVEYLOGISTIC
- 7. Survival Analysis with Complex Survey Data
- 8. Domain Estimation
- 9. Replication Techniques for Variance Estimation
- 10. Weight Adjustment Methods
- 11. Imputation Methods
- References
- Index