9780131465329

Applied Statistics and the SAS Programming Language

by ;
  • ISBN13:

    9780131465329

  • ISBN10:

    0131465325

  • Edition: 5th
  • Format: Paperback
  • Copyright: 3/30/2005
  • Publisher: Pearson

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Summary

As the SAScopy; programming language continues to evolve, this guide follows suit with timely coverage of the combination statistical package, database management system, and high-level programming language. Using current examples from business, medicine, education, and psychology,Applied Statistics and the SAS Programming Languageis an invaluable resource for applied researchers, giving them the capacity to perform statistical analyses with SAS without wading through pages of technical documentation.Includes the necessary SAS statements to run programs for most of the commonly used statistics, explanations of the computer output, interpretations of results, and examples of how to construct tables and write up results for reports and journal articles. Illustrated with SAS Graphtrade; output. Provides readers with ample models for developing programming skills.For anyone interested in learning more about applied statistics and the SAS programming language.

Table of Contents

Preface xiii
Acknowledgments xv
A SAS Tutorial
1(23)
Introduction
1(1)
Computing with SAS: An Illustrative Example
2(5)
Enhancing the Program
7(4)
SAS Procedures
11(2)
Overview of the SAS DATA Step
13(1)
Syntax of SAS Procedures
14(1)
Comment Statements
15(3)
References
18(6)
Problems
19(5)
Describing Data
24(45)
Introduction
24(1)
Describing Data
24(5)
More Descriptive Statistics
29(9)
Histograms, QQ Plots, and Probability Plots
38(3)
Descriptive Statistics Broken Down by Subgroups
41(2)
Frequency Distributions
43(2)
Bar Graphs
45(13)
Plotting Data
58(11)
Problems
64(5)
Analyzing Categorical Data
69(54)
Introduction
69(1)
Questionnaire Design and Analysis
70(5)
Adding Variable Labels
75(2)
Adding ``Value Labels'' (Formats)
77(5)
Recoding Data
82(3)
Using a Format to Recode a Variable
85(2)
Two-way Frequency Tables
87(4)
A Shortcut Way to Request Multiple Tables
91(1)
Computing Chi-square from Frequency Counts
92(1)
A Useful Program for Multiple Chi-square Tables
93(1)
A Useful Macro for Computing Chi-square from Frequency Counts
94(1)
McNemar's Test for Paired Data
95(4)
Computing the Kappa Statistics (Coefficient of Agreement)
99(1)
Odds Ratios
100(4)
Relative Risk
104(2)
Chi-square Test for Trend
106(2)
Mantel-Haenszel Chi-square for Stratified Tables and Meta-analysis
108(3)
``Check All That Apply'' Questions
111(12)
Problems
114(9)
Working with Date and Longitudinal Data
123(36)
Introduction
123(1)
Processing Date Variables
123(6)
Working with Two-digit Year Values (the Y2K Problem)
129(1)
Longitudinal Data
129(4)
Selecting the First or Last Visit per Patient
133(2)
Computing Differences between Observations in a Longitudinal Data Set
135(3)
Computing the Difference between the First and Last Observation for Each Subject
138(2)
Computing Frequencies on Longitudinal Data Sets
140(1)
Creating Summary Data Sets with Proc Means or Proc Summary
141(12)
Outputting Statistics Other Than Means
153(6)
Problems
154(5)
Correlation and Simple Regression
159(24)
Introduction
159(1)
Correlation
160(2)
Significance of a Correlation Coefficient
162(2)
How to Interpret a Correlation Coefficient
164(1)
Partial Correlations
165(1)
Linear Regression
166(3)
Partitioning the Total Sum of Squares
169(1)
Producing a Scatter Plot and the Regression Line
170(3)
Adding a Quadratic Term to the Regression Equation
173(1)
Transforming Data
174(9)
Problems
179(4)
T-tests and Nonparametric Comparisons
183(16)
Introduction
183(1)
T-test: Testing Differences between Two Means
183(3)
Random Assignment of Subjects
186(4)
Two Independent Samples: Distribution-free Tests
190(3)
One-tailed versus Two-tailed Tests
193(1)
Paired T-tests (Related Samples)
194(5)
Problems
196(3)
Analysis of Variance
199(37)
Introduction
199(1)
One-way Analysis of Variance
199(9)
Computing Contrasts
208(1)
Analysis of Variance: Two Independent Variables
209(5)
Interpreting Significant Interactions
214(8)
N-way Factorial Designs
222(1)
Unbalanced Designs: Proc GLM
223(4)
Analysis of Covariance
227(9)
Problems
231(5)
Repeated Measures Designs
236(46)
Introduction
236(1)
One-factor Experiments
237(6)
Using the Repeated Statement of Proc Anova
243(2)
Using Proc Mixed to Compute a Mixed (Random Effects) Model
245(2)
Two-factor Experiments with Repeated Measures on One Factor
247(11)
Two-factor Experiments with Repeated Measures on Both Factors
258(3)
Three-factor Experiments with a Repeated Measure on the Last Factor
261(7)
Three-factor Experiments with Repeated Measures on Two Factors
268(14)
Problems
278(4)
Multiple-Regression Analysis
282(38)
Introduction
282(1)
Designed Regression
283(5)
Nonexperimental Regression
288(3)
Stepwise and Other Variable Selection Methods
291(7)
Creating and Using Dummy Variables
298(2)
Using the Variance Inflation Factor to Look for Multicollinearity
300(1)
Logistic Regression
300(14)
Automatic Creation of Dummy Variables with Proc Logistic
314(6)
Problems
315(5)
Factor Analysis
320(16)
Introduction
320(1)
Types of Factor Analysis
320(1)
Principal Components Analysis
321(9)
Oblique Rotations
330(1)
Using Communalities Other Than One
331(2)
How to Reverse Item Scores
333(3)
Problems
335(1)
Psychometrics
336(17)
Introduction
336(1)
Using SAS to Score a Test
336(3)
Generalizing the Program for a Variable Number of Questions
339(3)
Creating a Better-looking Table Using Proc Tabulate
342(3)
A Complete Test-scoring and Item-analysis Program
345(3)
Test Reliability
348(1)
Interrater Reliability
349(4)
Problems
350(3)
The SAS Input Statement
353(23)
Introduction
353(1)
List Input: Data Values Separated by Spaces
353(1)
Reading Comma-delimited Data
354(1)
Using Informats with List Input
355(2)
Column Input
357(1)
Formatted Input
357(2)
Reading More Than One Line per Subject
359(1)
Changing the Order and Reading a Column More than Once
359(1)
Informat Lists
360(1)
``Holding the Line''---Single-and Double-trailing @s
361(1)
Suppressing the Error Messages for Invalid Data
362(1)
Reading ``Unstructured'' Data
363(13)
Problems
370(6)
External Files: Reading and Writing Raw and System Files
376(27)
Introduction
376(1)
Data in the Program Itself
377(1)
Reading Data from an External Text File (ASCII or EBCDIC)
378(2)
Infile Options
380(4)
Reading Data from Multiple Files (Using Wildcards)
384(1)
Writing ASCII or Raw Data to an External File
385(1)
Writing CSV (Comma-separated Variables) Files Using SAS
386(1)
Creating a Permanent SAS Data Set
387(1)
Reading Permanent SAS Data Sets
388(2)
How to Determine the Contents of a SAS Data Set
390(1)
Permanent SAS Data Sets with Formats
391(1)
Working with Large Data Sets
392(11)
Problems
400(3)
Data Set Subsetting, Concatenating, Merging, and Updating
403(14)
Introduction
403(1)
Subsetting
403(2)
Combining Similar Data from Multiple SAS Data Sets
405(1)
Combining Different Data from Multiple SAS Data Sets
406(3)
``Table Look Up''
409(3)
Updating a Master Data Set from an Update Data Set
412(5)
Problems
413(4)
Working with Arrays
417(15)
Introduction
417(1)
Substituting One Value for Another for a Series of Variables
417(2)
Extending Example 1 to Convert All Numeric Values of 999 to Missing
419(1)
Converting the Value of N/A (Not Applicable) to a Character Missing Value
420(1)
Converting Heights and Weights from English to Metric Units
421(1)
Temporary Arrays
422(2)
Using a Temporary Array to Score a Test
424(2)
Specifying Array Bounds
426(1)
Temporary Arrays and Array Bounds
426(1)
Implicitly Subscripted Arrays
427(5)
Problems
428(4)
Restructuring SAS Data Sets Using Arrays
432(12)
Introduction
432(1)
Creating a New Data Set with Several Observations per Subject from a Data Set with One Observation per Subject
433(2)
Another Example of Creating Multiple Observations from a Single Observation
435(1)
Going from One Observation per Subject to Many Observations per Subject Using Multidimensional Arrays
436(2)
Creating a Data Set with One Observation per Subject from a Data Set with Multiple Observations per Subject
438(2)
Creating a Data Set with One Observation per Subject from a Data Set with Multiple Observations per Subject Using a Multidimensional Array
440(4)
Problems
441(3)
A Review of SAS Functions: Functions Other than Character Functions
444(13)
Introduction
444(1)
Arithmetic and Mathematical Functions
444(2)
Random Number Functions
446(2)
Time and Date Functions
448(2)
The INPUT and PUT Functions: Converting Numeric to Character and Character to Numeric Variables
450(2)
The LAG and DIF Functions
452(5)
Problems
453(4)
A Review of SAS Functions: Character Functions
457(23)
Introduction
457(1)
How Lengths of Character Variables Are Set in a SAS Data Step
458(2)
Working with Blanks
460(1)
How to Remove Characters from a String
461(1)
Character Data Verification
462(1)
Substring Example
463(1)
Using the Substr Function on the Left-hand Side of the Equal Sign
464(1)
Doing the Previous Example Another Way
465(1)
Unpacking a String
465(1)
Parsing a String
466(1)
Locating the Position of One String Within Another String
467(1)
Changing Lowercase to Uppercase and Vice Versa
468(1)
Substituting One Character for Another
469(1)
Substituting One Word for Another in a String
470(1)
Concatenating (Joining) Strings
471(1)
Soundex Conversion
472(1)
Spelling Distance: The Spedis Function
473(7)
Problems
474(6)
Selected Programming Examples
480(15)
Introduction
480(1)
Expressing Data Values as a Percentage of the Grand Mean
480(2)
Expressing a Value as a Percentage of a Group Mean
482(1)
Plotting Means with Error Bars
483(2)
Using a Macro Variable to Save Coding Time
485(1)
Computing Relative Frequencies
485(2)
Computing Combined Frequencies on Different Variables
487(2)
Computing a Moving Average
489(2)
Sorting Within an Observation
491(1)
Computing Coefficient Alpha (or KR-20) in a Data Step
492(3)
Problems
494(1)
Syntax Examples
495(9)
Introduction
495(1)
Proc Anova
496(1)
Proc Append
496(1)
Proc Chart
496(1)
Proc Contents
497(1)
Proc Corr
497(1)
Proc Datasets
497(1)
Proc Factor
498(1)
Proc Format
498(1)
Proc Freq
499(1)
Proc Gchart
499(1)
Proc GLM
499(1)
Proc Gplot
500(1)
Proc Logistic
500(1)
Proc Means
500(1)
Proc Npar1way
501(1)
Proc Plot
501(1)
Proc Print
502(1)
Proc Rank
502(1)
Prog Reg
503(1)
Proc Sort
503(1)
Proc Ttest
503(1)
Proc Univariate
503(1)
Solutions to Odd-Numbered Problems 504(59)
Index 563

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