9781412925600

Statistical Analysis Quick Reference Guidebook : With SPSS Examples

by
  • ISBN13:

    9781412925600

  • ISBN10:

    1412925606

  • Format: Paperback
  • Copyright: 2006-08-10
  • Publisher: Sage Publications, Inc

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Supplemental Materials

What is included with this book?

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

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