Statistical Analysis Quick Reference Guidebook : With SPSS Examples

by Alan C. Elliott

• ISBN13: 9781412925600
• ISBN10: 1412925606
• Format: Paperback
• Copyright: 2006-08-10
• Publisher: Sage Publications, Inc

Summary

Statistical Analysis Quick Reference Guidebook: With SPSS Examples is a practical "cut to the chase" handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, authors Alan C. Elliott and Wayne A. Woodward provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results, and reporting outcomes.

Table of Contents

List of Tables and Figures	xiii
Acknowledgments	xix
1. Introduction	1	(22)
Getting the Most Out of This Quick Reference Guidebook	2	(1)
A Brief Review of the Statistical Process	3	(3)
Using Descriptive Statistics	4	(1)
Using Comparative Statistics	5	(1)
Using Correlational Statistics	5	(1)
Understanding Hypothesis Testing, Power, and Sample Size	6	(3)
Understanding the p-Value	9	(1)
Planning a Successful Analysis	10	(2)
Formulate a Testable Research Question (Hypothesis)	10	(1)
Collect Data Appropriate to Testing Your Hypotheses	10	(1)
Decide on the Type of Analysis Appropriate to Test Your Hypothesis	11	(1)
Properly Interpret and Report Your Results	12	(1)
Guidelines for Creating Data Sets	12	(4)
1. Decide What Variables You Need and Document Them	12	(1)
2. Design Your Data Set With One Subject (or Observation) Per Line	13	(1)
3. Each Variable Must Have a Properly Designated Name	14	(1)
4. Select Descriptive Labels for Each Variable	14	(1)
5. Select a Type for Each Variable	15	(1)
6. Additional Tips for Categorical (Character) Variables	15	(1)
7. Define Missing Values Codes	16	(1)
8. Consider the Need for a Grouping Variable	16	(1)
Preparing Excel Data for Import	16	(2)
Guidelines for Reporting Results	18	(1)
Guidelines for Creating and Using Graphs	19	(1)
Downloading Sample SPSS Data Files	20	(1)
Opening Data Files for Examples	20	(1)
Summary	20	(1)
References	21	(2)
2. Describing and Examining Data	23	(24)
Example Data Files	24	(1)
Describing Quantitative Data	24	(15)
Observe the Distribution of Your Data	25	(1)
Testing for Normality	25	(1)
Tips and Caveats for Quantitative Data	26	(1)
Quantitative Data Description Examples	27	(12)
EXAMPLE 2.1: Quantitative Data With an Unusual Value	28	(6)
EXAMPLE 2.2: Quantitative Data by Groups	34	(2)
EXAMPLE 2.3: Quantitative Data With Unusual Values	36	(3)
Describing Categorical Data	39	(6)
Considerations for Examining Categorical Data	39	(1)
Tips and Caveats	40	(1)
Describing Categorical Data Examples	40	(8)
EXAMPLE 2.4: Frequency Table for Categorical Data	40	(3)
EXAMPLE 2.5: Crosstabulation of Categorical Variables	43	(2)
Summary	45	(1)
References	45	(2)
3. Comparing One or Two Means Using the t-Test	47	(30)
One-Sample t-Test	48	(6)
Appropriate Applications for a One-Sample t-Test	48	(1)
Design Considerations for a One-Sample t-Test	48	(1)
Hypotheses for a One-Sample t-Test	49	(5)
EXAMPLE 3.1: One-Sample t-Test	50	(4)
Two-Sample t-Test	54	(14)
Appropriate Applications for a Two-Sample t-Test	54	(1)
Design Considerations for a Two-Sample t-Test	55	(1)
Hypotheses for a Two-Sample t-Test	56	(1)
Tips and Caveats for a Two-Sample t-Test	57	(1)
Interpreting Graphs Associated With the Two-Sample t-Test	58	(1)
Deciding Which Version of the t-Test Statistic to Use	58	(2)
Two-Sample t-Test Examples	60	(8)
EXAMPLE 3.2: Two-Sample t-Test With Equal Variances	60	(5)
EXAMPLE 3.3: Two-Sample t-Test With Variance Issues	65	(3)
Paired t-Test	68	(7)
Associated Confidence Interval	69	(1)
Appropriate Applications for a Paired t-Test	69	(1)
Design Considerations for a Paired t-Test	70	(1)
Hypotheses for a Paired t-Test	70	(8)
EXAMPLE 3.4: Paired t-Test	71	(4)
Summary	75	(1)
References	75	(2)
4. Correlation and Regression	77	(36)
Correlation Analysis	78	(9)
Appropriate Applications for Correlation Analysis	79	(1)
Design Considerations for Correlation Analysis	79	(1)
Hypotheses for Correlation Analysis	80	(1)
Tips and Caveats for Correlation Analysis	80	(7)
EXAMPLE 4.1: Correlation Analysis	83	(4)
Simple Linear Regression	87	(8)
Appropriate Applications for Simple Linear Regression	87	(1)
Design Considerations for Simple Linear Regression	88	(1)
Hypotheses for a Simple Linear Regression Analysis	89	(1)
Tips and Caveats for Simple Linear Regression	89	(2)
Interval Estimates	91	(4)
EXAMPLE 4.2: Simple Linear Regression	91	(4)
Multiple Linear Regression	95	(12)
Appropriate Applications of Multiple Linear Regression	96	(1)
Design Considerations for Multiple Linear Regression	96	(1)
Hypotheses for Multiple Linear Regression	97	(1)
R-Square	98	(1)
Model Selection Procedures for Multiple Linear Regression	99	(1)
Tips and Caveats for Multiple Linear Regression	100	(1)
Model Interpretation and Evaluation for Multiple Linear Regression	101	(4)
EXAMPLE 4.3: Multiple Linear Regression Analysis	102	(3)
Residual Analysis	105	(2)
Bland-Altman Analysis	107	(4)
Design Considerations for a Bland-Altman Analysis	108	(6)
EXAMPLE 4.4: Bland-Altman Analysis	108	(3)
Summary	111	(1)
References	112	(1)
5. Analysis of Categorical Data	113	(38)
Contingency Table Analysis (r x c)	114	(12)
Appropriate Applications of Contingency Table Analysis	114	(1)
Design Considerations for a Contingency Table Analysis	115	(1)
Hypotheses for a Contingency Table Analysis	116	(1)
Tips and Caveats for a Contingency Table Analysis	116	(1)
Contingency Table Examples	117	(9)
EXAMPLE 5.1: r x c Contingency Table Analysis	117	(6)
EXAMPLE 5.2: 2 x 2 Contingency Table Analysis	123	(3)
Analyzing Risk Ratios in a 2 x 2 Table	126	(5)
Appropriate Applications for Retrospective (Case Control) Studies	128	(1)
Appropriate Applications for Prospective (Cohort) Studies	128	(3)
EXAMPLE 5.3: Analyzing Risk Ratios for the Exposure/Reaction Data	128	(3)
McNemar's Test	131	(4)
Appropriate Applications of McNemar's Test	132	(1)
Hypotheses for McNemar's Test	132	(3)
EXAMPLE 5.4: McNemar's Test	133	(2)
Mantel-Haenszel Comparison	135	(5)
Appropriate Applications of the Mantel-Haenszel Procedure	136	(1)
Hypotheses Tests Used in Mantel-Haenszel Analysis	136	(1)
Design Considerations for a Mantel-Haenszel Test	136	(3)
EXAMPLE 5.5: Mantel-Haenszel Analysis	136	(3)
Tips and Caveats for Mantel-Haenszel Analysis	139	(1)
Tests of Interrater Reliability	140	(3)
Appropriate Applications of Interrater Reliability	140	(3)
EXAMPLE 5.6: Interrater Reliability Analysis	140	(3)
Goodness-of-Fit Test	143	(4)
Appropriate Applications of the Goodness-of-Fit Test	143	(1)
Design Considerations for a Goodness-of-Fit Test	144	(1)
Hypotheses for a Goodness-of-Fit Test	144	(1)
Tips and Caveats for a Goodness-of-Fit Test	144	(8)
EXAMPLE 5.7: Goodness-of-Fit Test	145	(2)
Other Measures of Association for Categorical Data	147	(2)
Summary	149	(1)
References	149	(2)
6. Analysis of Variance and Covariance	151	(40)
One-Way ANOVA	152	(14)
Appropriate Applications for a One-Way ANOVA	152	(1)
Design Considerations for a One-Way ANOVA	152	(2)
Hypotheses for a One-Way ANOVA	154	(1)
Tips and Caveats for a One-Way ANOVA	154	(12)
EXAMPLE 6.1: One-Way ANOVA	154	(8)
EXAMPLE 6.2: One-Way ANOVA With Trend Analysis	162	(4)
Two-Way Analysis of Variance	166	(9)
Appropriate Applications for a Two-Way ANOVA	167	(1)
Design Considerations for a Two-Way ANOVA	167	(1)
Hypotheses for a Two-Way ANOVA	168	(2)
Tips and Caveats for a Two-Way ANOVA	170	(5)
EXAMPLE 6.3: Two-Way ANOVA	171	(4)
Repeated-Measures Analysis of Variance	175	(7)
Appropriate Applications for a Repeated-Measures ANOVA	175	(1)
Design Considerations for a Repeated-Measures ANOVA	176	(1)
Hypotheses for a Repeated-Measures ANOVA	177	(1)
Tips and Caveats for a Repeated-Measures ANOVA	177	(5)
EXAMPLE 6.4: Repeated-Measures ANOVA	177	(5)
Analysis of Covariance	182	(8)
Appropriate Applications for Analysis of Covariance	182	(1)
Design Considerations for an Analysis of Covariance	182	(1)
Hypotheses for an Analysis of Covariance	183	(9)
EXAMPLE 6.5: Analysis of Covariance	184	(6)
Summary	190	(1)
References	190	(1)
7. Nonparametric Analysis Procedures	191	(18)
Spearman's Rho	192	(3)
Appropriate Applications for Spearman's Rho	192	(1)
Design Considerations for Spearman's Rho	193	(1)
Hypotheses for Spearman's Rho	193	(1)
Tips and Caveats for Spearman's Rho	193	(2)
EXAMPLE 7.1: Spearman's Rho	194	(1)
Mann-Whitney (Two Independent Groups Test)	195	(3)
Hypotheses for a Mann-Whitney Test	196	(2)
EXAMPLE 7.2: Mann-Whitney Test	196	(2)
Kruskal-Wallis Test	198	(3)
Hypotheses for a Kruskal-Wallis Test	198	(3)
EXAMPLE 7.3: Kruskal-Wallis Test	198	(3)
Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs	201	(3)
Hypotheses for a Sign Test or Wilcoxon Signed-Rank Test	202	(2)
EXAMPLE 7.4: Wilcoxon Signed-Rank Test and Sign Test	202	(2)
Friedman's Test	204	(3)
Hypotheses for Friedman's Test	204	(5)
EXAMPLE 7.5: Friedman's Test	204	(3)
Summary	207	(1)
References	207	(2)
8. Logistic Regression	209	(16)
Introduction to Logistic Regression	209	(2)
Appropriate Applications for Logistic Regression	210	(1)
Simple Logistic Regression	211	(4)
Hypotheses for Simple Logistic Regression	211	(1)
Tips and Caveats for Simple Logistic Regression	211	(4)
EXAMPLE 8.1: Simple Logistic Regression	212	(3)
Multiple Logistic Regression	215	(8)
Tips and Caveats for Multiple Logistic Regression	216	(4)
EXAMPLE 8.2: Multiple Logistic Regression	217	(3)
Interpretation of the Multiple Logistic Regression Model	220	(3)
Summary	223	(1)
References	223	(2)
Appendix A: A Brief Tutorial for Using SPSS for Windows	225	(18)
Working With Data in SPSS	227	(7)
SPSS Step-by-Step. EXAMPLE A1: Entering Data Into the SPSS Data Sheet	229	(2)
SPSS Step-by-Step. EXAMPLE A2: Importing a Data File From Microsoft Excel	231	(2)
SPSS Step-by-Step. EXAMPLE A3: Performing an Analysis	233	(1)
Transforming, Recoding, and Categorizing Your Data	234	(9)
SPSS Step-by-Step. EXAMPLE A4: Creating a New Variable Using Computation	234	(1)
SPSS Step-by-Step. EXAMPLE A5: Transforming Data to Make Data More Normally Distributed	235	(3)
SPSS Step-by-Step. EXAMPLE A6: Removing Selected Data From Analysis Using Filtering	238	(1)
SPSS Step-by-Step. EXAMPLE A7: Combining Groups and Creating Categories From Quantitative Data	239	(2)
SPSS Step-by-Step. EXAMPLE A8: Transposing Data	241	(2)
Appendix B: Choosing the Right Procedure to Use	243	(6)
How to Use the Tables	244	(5)
Index	249	(10)
About the Authors	259