[图书][B] Multiple imputation and its application
Multiple Imputation and its Application The most up-to-date edition of a bestselling guide to
analyzing partially observed data In this comprehensively revised Second Edition of Multiple …
analyzing partially observed data In this comprehensively revised Second Edition of Multiple …
[图书][B] Applied multiple imputation
K Kleinke, J Reinecke, D Salfrán, M Spiess - 2020 - Springer
Empirical data are seldom completely observed. How to adequately analyse data sets
affected by missing values is usually not the focus of courses at bachelor or master level …
affected by missing values is usually not the focus of courses at bachelor or master level …
Multiple imputation: a primer
JL Schafer - Statistical methods in medical research, 1999 - journals.sagepub.com
Multiple imputation: a primer - Joseph L Schafer, 1999 Skip to main content Intended for
healthcare professionals Sage Journals Home Search this journal Search all journals Enter …
healthcare professionals Sage Journals Home Search this journal Search all journals Enter …
Multiple imputation in multivariate research
Statistical analysis with missing data has always been a challenge. However, there have
been tremendous advances in statistical theory related to analysis with missing data. Of …
been tremendous advances in statistical theory related to analysis with missing data. Of …
Recovery of information from multiple imputation: a simulation study
Background Multiple imputation is becoming increasingly popular for handling missing data.
However, it is often implemented without adequate consideration of whether it offers any …
However, it is often implemented without adequate consideration of whether it offers any …
[PDF][PDF] An overview of multiple imputation
DB Rubin - Proceedings of the survey research methods section of …, 1988 - Citeseer
Multiple imputation for nonresponse in public-use files replaces each missing value by two
or more plausible values. The values can be chosen to represent both uncertainty about …
or more plausible values. The values can be chosen to represent both uncertainty about …
Multiple imputation for missing data in a longitudinal cohort study: a tutorial based on a detailed case study involving imputation of missing outcome data
Multiple imputation (MI), a two-stage process whereby missing data are imputed multiple
times and the resulting estimates of the parameter (s) of interest are combined across the …
times and the resulting estimates of the parameter (s) of interest are combined across the …
Sensitivity analysis after multiple imputation under missing at random: a weighting approach
JR Carpenter, MG Kenward… - Statistical methods in …, 2007 - journals.sagepub.com
Multiple imputation (MI) is now well established as a flexible, general, method for the
analysis of data sets with missing values. Most implementations assume the missing data …
analysis of data sets with missing values. Most implementations assume the missing data …
Multiple imputation of missing values
P Royston - The Stata Journal, 2004 - journals.sagepub.com
Following the seminal publications of Rubin about thirty years ago, statisticians have
become increasingly aware of the inadequacy of “complete-case” analysis of datasets with …
become increasingly aware of the inadequacy of “complete-case” analysis of datasets with …
Multiple imputation with missing data indicators
Multiple imputation is a well-established general technique for analyzing data with missing
values. A convenient way to implement multiple imputation is sequential regression multiple …
values. A convenient way to implement multiple imputation is sequential regression multiple …