Performing Data Analysis Using Ibm Spss

Informationen zum Autor LAWRENCE S. MEYERS, PhD, is Professor in the Depart-ment of Psychology at California State University, Sacramento. The author of numerous books, Dr. Meyers is a member of the Association for Psychological Science and the Society for Industrial and Organiza-tional Psychology.GLENN C. GAMST, PhD, is Chair and Professor in the Department of Psychology at the University of La Verne. His research interests include univariate and multivariate statistics as well as multicultural community mental health outcome research.A. J. Guarino, PhD, is Professor of Biostatistics at Massachusetts General Hospital, Institute of Health Professions, where he serves as the methodologist for capstones and dissertations as well as teaching advanced Biostatistics courses. Dr. Guarino is also the statistician on numerous National Institutes of Health grants and coauthor of several statistical textbooks. Klappentext Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS(r)Performing Data Analysis Using IBM SPSS(r) uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Data entry procedures, variable naming, and step-by-step instructions for all analyses are provided in addition to IBM SPSS point-and-click methods, including details on how to view and manipulate output.Designed as a user's guide for students and other interested readers to perform statistical data analysis with IBM SPSS, this book addresses the needs, level of sophistication, and interest in introductory statistical methodology on the part of readers in social and behavioral science, business, health-related, and education programs. Each chapter of Performing Data Analysis Using IBM SPSS covers a particular statistical procedure and offers the following: an example problem or analysis goal, together with a data set; IBM SPSS analysis with step-by-step analysis setup and accompanying screen shots; and IBM SPSS output with screen shots and narrative on how to read or interpret the results of the analysis.The book provides in-depth chapter coverage of:* IBM SPSS statistical output* Descriptive statistics procedures* Score distribution assumption evaluations* Bivariate correlation* Regressing (predicting) quantitative and categorical variables* Survival analysis* t Test* ANOVA and ANCOVA* Multivariate group differences* Multidimensional scaling* Cluster analysis* Nonparametric procedures for frequency dataPerforming Data Analysis Using IBM SPSS is an excellent text for upper-undergraduate and graduate-level students in courses on social, behavioral, and health sciences as well as secondary education, research design, and statistics. Also an excellent reference, the book is ideal for professionals and researchers in the social, behavioral, and health sciences; applied statisticians; and practitioners working in industry. Zusammenfassung Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS(R) Performing Data Analysis Using IBM SPSS(R) uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets. Inhaltsverzeichnis PREFACE ixPART 1 GETTING STARTED WITH IBM SPSS(r) 1CHAPTER 1 INTRODUCTION TO IBM SPSS(r) 3CHAPTER 2 ENTERING DATA IN IBM SPSS(r) 5CHAPTER 3 IMPORTING DATA FROM EXCEL TO IBM SPSS(r) 15PART 2 OBTAINING, EDITING, AND SAVING STATISTICAL OUTPUT 19CHAPTER 4 PERFORMING STATISTICAL PROCEDURES IN IBM SPSS(r) 21CHAPTER 5 EDITING OUTPUT 27CHAPTER 6 SAVING AND COPYING OUTPUT 31PART 3 MANIPULATING DATA 37CHAPTER 7 SORTING AND SELECTING CASES 39CHAPTER 8 SPLITTING DATA FILES 45CHAPTER 9 MERGING DATA FROM SEPARATE FILES 51PART 4 DESCRIPTIVE STATISTICS PROCEDURES 57CHAPTER 10 FREQUENCIES 59CHAPTER 11 DESCRIPTIVES 67CHAPTER 12 EXPLORE 71PART 5 SIMPLE DATA TRANSFOR...

List of contents

PREFACE ix
 
PART 1 GETTING STARTED WITH IBM SPSS(r) 1
 
CHAPTER 1 INTRODUCTION TO IBM SPSS(r) 3
 
CHAPTER 2 ENTERING DATA IN IBM SPSS(r) 5
 
CHAPTER 3 IMPORTING DATA FROM EXCEL TO IBM SPSS(r) 15
 
PART 2 OBTAINING, EDITING, AND SAVING STATISTICAL OUTPUT 19
 
CHAPTER 4 PERFORMING STATISTICAL PROCEDURES IN IBM SPSS(r) 21
 
CHAPTER 5 EDITING OUTPUT 27
 
CHAPTER 6 SAVING AND COPYING OUTPUT 31
 
PART 3 MANIPULATING DATA 37
 
CHAPTER 7 SORTING AND SELECTING CASES 39
 
CHAPTER 8 SPLITTING DATA FILES 45
 
CHAPTER 9 MERGING DATA FROM SEPARATE FILES 51
 
PART 4 DESCRIPTIVE STATISTICS PROCEDURES 57
 
CHAPTER 10 FREQUENCIES 59
 
CHAPTER 11 DESCRIPTIVES 67
 
CHAPTER 12 EXPLORE 71
 
PART 5 SIMPLE DATA TRANSFORMATIONS 77
 
CHAPTER 13 STANDARDIZING VARIABLES TO Z SCORES 79
 
CHAPTER 14 RECODING VARIABLES 83
 
CHAPTER 15 VISUAL BINNING 97
 
CHAPTER 16 COMPUTING NEW VARIABLES 103
 
CHAPTER 17 TRANSFORMING DATES TO AGE 111
 
PART 6 EVALUATING SCORE DISTRIBUTION ASSUMPTIONS 121
 
CHAPTER 18 DETECTING UNIVARIATE OUTLIERS 123
 
CHAPTER 19 DETECTING MULTIVARIATE OUTLIERS 131
 
CHAPTER 20 ASSESSING DISTRIBUTION SHAPE: NORMALITY, SKEWNESS, AND KURTOSIS 139
 
CHAPTER 21 TRANSFORMING DATA TO REMEDY STATISTICAL ASSUMPTION VIOLATIONS 147
 
PART 7 BIVARIATE CORRELATION 157
 
CHAPTER 22 PEARSON CORRELATION 159
 
CHAPTER 23 SPEARMAN RHO AND KENDALL TAU-B RANK-ORDER CORRELATIONS 165
 
PART 8 REGRESSING (PREDICTING) QUANTITATIVE VARIABLES 171
 
CHAPTER 24 SIMPLE LINEAR REGRESSION 173
 
CHAPTER 25 CENTERING THE PREDICTOR VARIABLE IN SIMPLE LINEAR REGRESSION 181
 
CHAPTER 26 MULTIPLE LINEAR REGRESSION 191
 
CHAPTER 27 HIERARCHICAL LINEAR REGRESSION 211
 
CHAPTER 28 POLYNOMIAL REGRESSION 217
 
CHAPTER 29 MULTILEVEL MODELING 225
 
PART 9 REGRESSING (PREDICTING) CATEGORICAL VARIABLES 253
 
CHAPTER 30 BINARY LOGISTIC REGRESSION 255
 
CHAPTER 31 ROC ANALYSIS 265
 
CHAPTER 32 MULTINOMINAL LOGISTIC REGRESSION 273
 
PART 10 SURVIVAL ANALYSIS 281
 
CHAPTER 33 SURVIVAL ANALYSIS: LIFE TABLES 283
 
CHAPTER 34 THE KAPLAN-MEIER SURVIVAL ANALYSIS 289
 
CHAPTER 35 COX REGRESSION 301
 
PART 11 RELIABILITY AS A GAUGE OF MEASUREMENT QUALITY 309
 
CHAPTER 36 RELIABILITY ANALYSIS: INTERNAL CONSISTENCY 311
 
CHAPTER 37 RELIABILITY ANALYSIS: ASSESSING RATER CONSISTENCY 319
 
PART 12 ANALYSIS OF STRUCTURE 329
 
CHAPTER 38 PRINCIPAL COMPONENTS AND FACTOR ANALYSIS 331
 
CHAPTER 39 CONFIRMATORY FACTOR ANALYSIS 353
 
PART 13 EVALUATING CAUSAL (PREDICTIVE) MODELS 379
 
CHAPTER 40 SIMPLE MEDIATION 381
 
CHAPTER 41 PATH ANALYSIS USING MULTIPLE REGRESSION 389
 
CHAPTER 42 PATH ANALYSIS USING STRUCTURAL EQUATION MODELING 397
 
CHAPTER 43 STRUCTURAL EQUATION MODELING 419
 
PART 14 t TEST 457
 
CHAPTER 44 ONE-SAMPLE t TEST 459
 
CHAPTER 45 INDEPENDENT-SAMPLES t TEST 463
 
CHAPTER 46 PAIRED-SAMPLES t TEST 471
 
PART 15 UNIVARIATE GROUP DIFFERENCES: ANOVA AND ANCOVA 475
 
CHAPTER 47 ONE-WAY BETWEEN-SUBJECTS ANOVA 477
 
CHAPTER 48 POLYNOMIAL TREND ANALYSIS 485
 
CHAPTER 49 ONE-WAY BETWEEN-SUBJECTS ANCOVA 493
 
CHAPTER 50 TWO-WAY BETWEEN-SUBJECTS ANOVA 507
 
CHAPTER 51 ONE-WAY WITHIN-SUBJECTS ANOVA 521
 
CHAPTER 52 REPEATED MEASURES USING LINEAR MIXED MODELS 531
 
CHAPTER 53 TWO-WAY MIXED ANOVA 555
 
PART 16 MULTIVARIATE GROUP DIFFERENCES: MANOVA AND DISC

Product details

• Authors: Gamst, Glenn Gamst, Glenn C Gamst, Glenn C. Gamst, Guarino, A J Guarino, A. J. Guarino, Guarino A. J., Meyers, L. S. Meyers, Lawrence Meyers, Lawrence S Meyers, Lawrence S. Meyers, Lawrence S. Gamst Meyers, Ls Meyers, Meyers Lawrence S.
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Paperback / Softback
• Released: 27.09.2013
• EAN: 9781118357019
• ISBN: 978-1-118-35701-9
• No. of pages: 736
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Statistik, Datenanalyse, Data Mining, Statistics, data analysis, Data Mining Statistics