Comparison of Random Forest and Parametric Imputation Models for Imputing Missing Data Using MICE: A CALIBER Study is a research paper published in American Journal of Epidemiology (2014). On theSindex it has a DataRank of 1.0. It has been cited 830 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
1.0
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →Medical Research Council
Grant: MC_EX_G0800814
Medical Research Council
Grant: MR/K02180X/1
Wellcome Trust
Grant: 086091
Higher resolution cardiovascular epidemiology: unique insights from linking the national cardiac event register with primary care records and highly phenotyped cohorts.
Medical Research Council
Grant: G0900724
Developing and disseminating robust methods for handling missing data in epidemiological studies
Medical Research Council
Grant: MR/K006584/1
Centre for Health service and Academic Partnership in Translational eHealth Research (CHAPTER)
Wellcome Trust
Grant: 0938/30/Z/10/Z
Medical Research Council
Grant: G0902393
Prognosis Research: A Strategic Initiative in Translational Pathways (PROGRESS)
Wellcome Trust
Grant: 086091/Z/08/Z
Economic and Social Research Council
Grant: ES/G026300/1
Wellcome Trust
Grant: 093830
Economic and Social Research Council
Grant: ES/H022252/1
National Institute for Health Research (NIHR)
Grant: RP-PG-0407-10314
FWCI
13.38
Citation Percentile
1.0%
Influential Citations
36
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals