Applied Statistics and the SAS Programming Language

by Cody, Ron P.; Smith, Jeffrey K.

• ISBN13: 9780131465329
• ISBN10: 0131465325
• Edition: 5th
• Format: Paperback
• Copyright: 2005-03-30
• Publisher: Pearson

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