Multiple Imputation of Missing Data Using SAS
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Sprache:Englisch
30,99 €
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Produktdetails
Format
ePUB
Kopierschutz
Ja
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
01.07.2014
Verlag
SAS InstituteSeitenzahl
164 (Printausgabe)
Dateigröße
15234 KB
Sprache
Englisch
EAN
9781629592039
Find guidance on using SAS for multiple imputation and solving common missing data issues.
Multiple Imputation of Missing Data Using SAS provides both theoretical background and constructive solutions for those working with incomplete data sets in an engaging example-driven format. It offers practical instruction on the use of SAS for multiple imputation and provides numerous examples that use a variety of public release data sets with applications to survey data.
Written for users with an intermediate background in SAS programming and statistics, this book is an excellent resource for anyone seeking guidance on multiple imputation. The authors cover the MI and MIANALYZE procedures in detail, along with other procedures used for analysis of complete data sets. They guide analysts through the multiple imputation process, including evaluation of missing data patterns, choice of an imputation method, execution of the process, and interpretation of results.
Topics discussed include how to deal with missing data problems in a statistically appropriate manner, how to intelligently select an imputation method, how to incorporate the uncertainty introduced by the imputation process, and how to incorporate the complex sample design (if appropriate) through use of the SAS SURVEY procedures.
Discover the theoretical background and see extensive applications of the multiple imputation process in action.
This book is part of the SAS Press program.
Multiple Imputation of Missing Data Using SAS provides both theoretical background and constructive solutions for those working with incomplete data sets in an engaging example-driven format. It offers practical instruction on the use of SAS for multiple imputation and provides numerous examples that use a variety of public release data sets with applications to survey data.
Written for users with an intermediate background in SAS programming and statistics, this book is an excellent resource for anyone seeking guidance on multiple imputation. The authors cover the MI and MIANALYZE procedures in detail, along with other procedures used for analysis of complete data sets. They guide analysts through the multiple imputation process, including evaluation of missing data patterns, choice of an imputation method, execution of the process, and interpretation of results.
Topics discussed include how to deal with missing data problems in a statistically appropriate manner, how to intelligently select an imputation method, how to incorporate the uncertainty introduced by the imputation process, and how to incorporate the complex sample design (if appropriate) through use of the SAS SURVEY procedures.
Discover the theoretical background and see extensive applications of the multiple imputation process in action.
This book is part of the SAS Press program.
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