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Multiple Imputation in Practice: With Examples Using IVEware
provides practical guidance on multiple imputation analysis, from
simple to complex problems using real and simulated data sets. Data
sets from cross-sectional, retrospective, prospective and
longitudinal studies, randomized clinical trials, complex sample
surveys are used to illustrate both simple, and complex analyses.
Version 0.3 of IVEware, the software developed by the University of
Michigan, is used to illustrate analyses. IVEware can multiply
impute missing values, analyze multiply imputed data sets,
incorporate complex sample design features, and be used for other
statistical analyses framed as missing data problems. IVEware can
be used under Windows, Linux, and Mac, and with software packages
like SAS, SPSS, Stata, and R, or as a stand-alone tool. This book
will be helpful to researchers looking for guidance on the use of
multiple imputation to address missing data problems, along with
examples of correct analysis techniques.
Multiple Imputation in Practice: With Examples Using IVEware
provides practical guidance on multiple imputation analysis, from
simple to complex problems using real and simulated data sets. Data
sets from cross-sectional, retrospective, prospective and
longitudinal studies, randomized clinical trials, complex sample
surveys are used to illustrate both simple, and complex analyses.
Version 0.3 of IVEware, the software developed by the University of
Michigan, is used to illustrate analyses. IVEware can multiply
impute missing values, analyze multiply imputed data sets,
incorporate complex sample design features, and be used for other
statistical analyses framed as missing data problems. IVEware can
be used under Windows, Linux, and Mac, and with software packages
like SAS, SPSS, Stata, and R, or as a stand-alone tool. This book
will be helpful to researchers looking for guidance on the use of
multiple imputation to address missing data problems, along with
examples of correct analysis techniques.
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