10.1371/journal.pone.0139210.t004
Katya L. Masconi
Katya
L. Masconi
Tandi Edith Matsha-Erasmus
Tandi Edith
Matsha-Erasmus
Rajiv T. Erasmus
Rajiv
T. Erasmus
Andre P. Kengne
Andre
P. Kengne
Characteristics comparison of participants for five multiple imputation datasets.
Public Library of Science
2015
Rotterdam Predictive model
undiagnosed diabetes
South Africa BackgroundImputation techniques
undiagnosed diabetes risk prediction models
Kuwaiti Risk model
Data Imputation Techniques
Cambridge Diabetes Risk model
imputation methods
Omani Diabetes Risk model
intercept adjustment.ResultsThe study sample
data
2015-09-25 05:17:04
Dataset
https://plos.figshare.com/articles/dataset/_Characteristics_comparison_of_participants_for_five_multiple_imputation_datasets_/1557821
<p>Characteristics comparison of participants for five multiple imputation datasets.</p>