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Data Analysis with IBM SPSS Statistics

You're reading from   Data Analysis with IBM SPSS Statistics Implementing data modeling, descriptive statistics and ANOVA

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787283817
Length 446 pages
Edition 1st Edition
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Authors (2):
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Ken Stehlik-Barry Ken Stehlik-Barry
Author Profile Icon Ken Stehlik-Barry
Ken Stehlik-Barry
Anthony Babinec Anthony Babinec
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Anthony Babinec
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Toc

Table of Contents (17) Chapters Close

Preface 1. Installing and Configuring SPSS FREE CHAPTER 2. Accessing and Organizing Data 3. Statistics for Individual Data Elements 4. Dealing with Missing Data and Outliers 5. Visually Exploring the Data 6. Sampling, Subsetting, and Weighting 7. Creating New Data Elements 8. Adding and Matching Files 9. Aggregating and Restructuring Data 10. Crosstabulation Patterns for Categorical Data 11. Comparing Means and ANOVA 12. Correlations 13. Linear Regression 14. Principal Components and Factor Analysis 15. Clustering 16. Discriminant Analysis

Listwise versus pairwise missing values

As was shown in the first correlation matrix earlier in the chapter, missing values are, by default, handled in a pairwise manner in the correlation procedure. In linear regression, the default is to exclude cases on a listwise basis. While the default setting can be changed in each of these procedures, it is important to appreciate the differences and decide how to best handle this aspect of the analysis process.

The pairwise approach makes use of all the available information, so it provides the most complete picture of the linear relationship between a pair of variables. Listwise handling of missing values creates a matrix in which each coefficient is based on the same set of observations, which provides consistency.

Comparing pairwise and...

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