Nijman, SWJ;
Groenhof, TKJ;
Hoogland, J;
Bots, ML;
Brandjes, M;
Jacobs, JJL;
Asselbergs, FW;
... Debray, TPA; + view all
(2021)
Real-time imputation of missing predictor values improved the application of prediction models in daily practice.
Journal of Clinical Epidemiology
, 134
pp. 22-34.
10.1016/j.jclinepi.2021.01.003.
(In press).
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Abstract
OBJECTIVES: In clinical practice, many prediction models cannot be used when predictor values are missing. We, therefore, propose and evaluate methods for real-time imputation. STUDY DESIGN AND SETTING: We describe (i) mean imputation (where missing values are replaced by the sample mean), (ii) joint modeling imputation (JMI, where we use a multivariate normal approximation to generate patient-specific imputations), and (iii) conditional modeling imputation (CMI, where a multivariable imputation model is derived for each predictor from a population). We compared these methods in a case study evaluating the root mean squared error (RMSE) and coverage of the 95% confidence intervals (i.e., the proportion of confidence intervals that contain the true predictor value) of imputed predictor values. RESULTS: -RMSE was lowest when adopting JMI or CMI, although imputation of individual predictors did not always lead to substantial improvements as compared to mean imputation. JMI and CMI appeared particularly useful when the values of multiple predictors of the model were missing. Coverage reached the nominal level (i.e., 95%) for both CMI and JMI. CONCLUSION: Multiple imputations using either CMI or JMI is recommended when dealing with missing predictor values in real-time settings.
| Type: | Article |
|---|---|
| Title: | Real-time imputation of missing predictor values improved the application of prediction models in daily practice |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.jclinepi.2021.01.003 |
| Publisher version: | http://dx.doi.org/10.1016/j.jclinepi.2021.01.003 |
| Language: | English |
| Additional information: | © 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Computerized decision support system, Electronic health records, Missing data, Multiple imputations, Prediction, Real-time imputation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10123056 |
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