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Item Details
| Title:
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MISSING DATA
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| By: |
Paul D. Allison |
| Format: |
Electronic book text |
| List price:
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£12.99 |
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We believe that this item is permanently unavailable, and so we cannot source
it.
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| ISBN 10: |
1452207909 |
| ISBN 13: |
9781452207902 |
| Publisher: |
SAGE PUBLICATIONS INC EBOOKS |
| Pub. date: |
18 April, 2013 |
| Edition: |
1st edition |
| Series: |
Quantitative Applications in the Social Sciences 136 |
| Description: |
Using numerous examples and practical tips, this book offers a nontechnical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer (and, better) methods, maximum likelihood and multiple imputation. Anyone who has relied on ad-hoc methods that are statistically inefficient or biased will find this book a welcome and accessible solution to their problems with handling missing data. |
| Synopsis: |
Sooner or later anyone who does statistical analysis runs into problems with missing data in which information for some variables is missing for some cases. Why is this a problem? Because most statistical methods presume that every case has information on all the variables to be included in the analysis. Using numerous examples and practical tips, this book offers a non-technical explanation of the standard methods for missing data (such as listwise or casewise deletion) as well as two newer (and, better) methods, maximum likelihood and multiple imputation. Anyone who has been relying on ad-hoc methods that are statistically inefficient or biased will find this book a welcome and accessible solution to their problems with handling missing data. |
| Publication: |
US |
| Imprint: |
SAGE Publications Inc |
| Returns: |
Non-returnable |
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