000			03855nam a2200397 a 4500
001			7199
003			BD-DhEWU
005			20190103020002.0
008			130905s2010 fluab g b 001 0 eng d
010			_a 2009020819
020			_a9781420070576 (hard back : alk. paper)
020			_a1420070576 (hard back : alk. paper)
035			_a(OCoLC) 166872496
040			_aDLC _cDLC _dBTCTA _dBAKER _dYDXCP _dC#P _dBWX _dCDX _dNLGGC _dBD-DhEWU _beng
041			_aeng
050	0	0	_aQA76.73.S27 _bK54 2010
082	0	4	_a610.72 KLS _222 _b2010
084			_a54.50 _2bcl
100	1		_aKleinman, Ken. _92307
245	1	0	_aSAS and R : _bdata management, statistical analysis, and graphics / _cKen Kleinman, Nicholas J. Horton.
260			_aBoca Raton : _bCRC Press, _cc2010.
300			_axix, 323 p. : _bill., map ; _c27 cm.
500			_a"A Chapman & Hall book."
504			_aIncludes bibliographical references and indexes.
505			_aData Management Input Output Structure and Meta-Data Derived Variables and Data Manipulation Merging, Combining, and Subsetting Data Sets Date and Time Variables Interactions with the Operating System Mathematical Functions Matrix Operations Probability Distributions and Random Number Generation Control Flow, Programming, and Data Generation Common Statistical Procedures Summary Statistics Bivariate Statistics Contingency Tables Two Sample Tests for Continuous Variables Linear Regression and ANOVA Model Fitting Model Comparison and Selection Tests, Contrasts, and Linear Functions of Parameters Model Diagnostics Model Parameters and Results Regression Generalizations Generalized Linear Models Models for Correlated Data Survival Analysis Further Generalizations to Regression Models Graphics A Compendium of Useful Plots Adding Elements Options and Parameters Saving Graphs Other Topics and Extended Examples Power and Sample Size Calculations Generate Data from Generalized Linear Random Effects Model Generate Correlated Binary Data Read Variable Format Files and Plot Maps Missing Data: Multiple Imputation Bayesian Poisson Regression Multivariate Statistics and Discriminant Procedures Complex Survey Design Appendix A: Introduction to SAS Installation Running SAS and a Sample Session Learning SAS and Getting Help Fundamental Structures: Data Step, Procedures, and Global Statements Work Process: The Cognitive Style of SAS Useful SAS Background Accessing and Controlling SAS Output: The Output Delivery System The SAS Macro Facility: Writing Functions and Passing Values Miscellanea Appendix B: Introduction to R Installation Running R and Sample Session Learning R and Getting Help Fundamental Structures: Objects, Classes, and Related Concepts Built-in and User-Defined Functions Add-ons: Libraries and Packages Support and Bugs Appendix C: The HELP Study Data Set Background on the HELP Study Roadmap to Analyses of the HELP Data Set Detailed Description of the Data Set Appendix D: References Appendix E: Indices Subject Index SAS Index R Index Further Resources and HELP Examples appear at the end of each chapter.
520			_aPresents a different way to learn how to perform an analytical task in both SAS and R. This book covers many common tasks, along with more complex applications. It provides parallel examples in SAS and R to demonstrate how to use the software and derive identical answers regardless of software choice.
526			_aAS
590			_aTahur Ahmed
650		0	_aSAS (Computer program language) _2SLSH _92308
650		0	_aR (Computer program language) _2SLSH _92309
700	1		_aHorton, Nicholas J. _92310
856			_3OCLC _uhttp://www.worldcat.org/title/sas-and-r-data-management-statistical-analysis-and-graphics/oclc/166872496&referer=brief_results
856	4	0	_3Ebook Fulltext _uhttp://lib.ewubd.edu/ebook/7199
942			_2ddc _cTEXT _02
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