Impact of Imputation of Missing Data on Estimation of Survival Rates: An Example in Breast Cancer
Loading...
Date
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Brieflands
Abstract
Background: Multifactorial regression models are frequently used in medicine to estimate survival rate of patients across risk groups. However, their results are not generalisable, if in the development of models assumptions required are not satisfied. Missing data is a common problem in pathology. The aim of this paper is to address the danger of exclusion of cases with missing data, and to highlight the importance of imputation of missing data before development of multifactorial models.