Multiple imputation of missing data continues to be a topic of considerable interest and importance to applied researchers. In this article, the ice package for multiple imputation is further updated. Special attention in this article is paid to imputing interval-censored observations, and a suggestion to use imputation of right-censored survival data to elucidate covariate effects graphically
Royston (2004) introduced mvis, an implementation for Stata of MICE, a method of multiple multivaria...
International audienceRelative survival assesses the effects of prognostic factors on disease-specif...
International audienceRelative survival assesses the effects of prognostic factors on disease-specif...
Multiple imputation of missing data continues to be a topic of considerable interest and importance ...
Multiple imputation of missing data continues to be a topic of considerable interest and importance ...
Multiple imputation of missing data continues to be a topic of considerable interest and importance ...
Following the seminal publications of Rubin about thirty years ago, statisticians have become increa...
Following the seminal publications of Rubin about thirty years ago, statisticians have become increa...
In survival analysis, censored observations can be regarded as missing event time data. For analysis...
In survival analysis, censored observations can be regarded as missing event time data. For analysis...
Multiple imputation (MI) is a commonly used approach to impute missing data. This thesis studies mis...
Missing data are a common occurrence in real datasets. For epidemiological and prognostic factors st...
Royston (2004) introduced mvis, an implementation for Stata of MICE, a method of multiple multivaria...
Multiple imputation (MI) is a commonly used approach to impute missing data. This thesis studies mis...
2013-08-05The presence of censoring is one common but critical feature for survival data. Traditiona...
Royston (2004) introduced mvis, an implementation for Stata of MICE, a method of multiple multivaria...
International audienceRelative survival assesses the effects of prognostic factors on disease-specif...
International audienceRelative survival assesses the effects of prognostic factors on disease-specif...
Multiple imputation of missing data continues to be a topic of considerable interest and importance ...
Multiple imputation of missing data continues to be a topic of considerable interest and importance ...
Multiple imputation of missing data continues to be a topic of considerable interest and importance ...
Following the seminal publications of Rubin about thirty years ago, statisticians have become increa...
Following the seminal publications of Rubin about thirty years ago, statisticians have become increa...
In survival analysis, censored observations can be regarded as missing event time data. For analysis...
In survival analysis, censored observations can be regarded as missing event time data. For analysis...
Multiple imputation (MI) is a commonly used approach to impute missing data. This thesis studies mis...
Missing data are a common occurrence in real datasets. For epidemiological and prognostic factors st...
Royston (2004) introduced mvis, an implementation for Stata of MICE, a method of multiple multivaria...
Multiple imputation (MI) is a commonly used approach to impute missing data. This thesis studies mis...
2013-08-05The presence of censoring is one common but critical feature for survival data. Traditiona...
Royston (2004) introduced mvis, an implementation for Stata of MICE, a method of multiple multivaria...
International audienceRelative survival assesses the effects of prognostic factors on disease-specif...
International audienceRelative survival assesses the effects of prognostic factors on disease-specif...