Applied Statistics and the SAS Programming Language

ISBN 13:
9780131465329
ISBN 10:
0131465325
Edition: 5th
Format: Paperback
Copyright: 03/30/2005
Publisher: Pearson

Note: Not guaranteed to come with supplemental materials (access cards, study guides, lab manuals, CDs, etc.)

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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.

Preface

xiii

Acknowledgments

A SAS Tutorial

(23)

Introduction

(1)

Computing with SAS: An Illustrative Example

(5)

Enhancing the Program

(4)

SAS Procedures

(2)

Overview of the SAS DATA Step

(1)

Syntax of SAS Procedures

(1)

Comment Statements

(3)

References

(6)

Problems

(5)

Describing Data

(45)

Introduction

(1)

Describing Data

(5)

More Descriptive Statistics

(9)

Histograms, QQ Plots, and Probability Plots

(3)

Descriptive Statistics Broken Down by Subgroups

(2)

Frequency Distributions

(2)

Bar Graphs

(13)

Plotting Data

(11)

Problems

(5)

Analyzing Categorical Data

(54)

Introduction

(1)

Questionnaire Design and Analysis

(5)

Adding Variable Labels

(2)

Adding ``Value Labels'' (Formats)

(5)

Recoding Data

(3)

Using a Format to Recode a Variable

(2)

Two-way Frequency Tables

(4)

A Shortcut Way to Request Multiple Tables

(1)

Computing Chi-square from Frequency Counts

(1)

A Useful Program for Multiple Chi-square Tables

(1)

A Useful Macro for Computing Chi-square from Frequency Counts

(1)

McNemar's Test for Paired Data

(4)

Computing the Kappa Statistics (Coefficient of Agreement)

(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

Applied Statistics and the SAS Programming Language

9780131465329

0131465325

Summary

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Applied Statistics and the SAS Programming Language

9780131465329

0131465325

Summary

Table of Contents

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