Letter to the EditorImputation is beneficial for handling missing data in predictive models
References (4)
Bias arising from missing data in predictive models
J Clin Epidemiol
(2006)- et al.
Statistical analysis with missing data
(1987)
Cited by (79)
Diffusion basis spectrum imaging predicts long-term clinical outcomes following surgery in cervical spondylotic myelopathy
2023, Spine JournalCitation Excerpt :Nonoverlapping 95% confidence intervals between feature sets for a given performance metric (eg, accuracy) were considered statistically significantly different [33]. Missing data from patient-reported outcome questionnaires (<0.5%) were statistically imputed via single regression imputation [34] based on predictive mean matching (mice package R) [34–37]. All statistical analyses were performed in Python and R, version 4.1.4.
Risk factor analysis for “diagnosis not reached” results from bovine samples submitted to British veterinary laboratories in 2013–2017
2020, Preventive Veterinary MedicineCitation Excerpt :The main concern in the present study was related to the loss of precision and power due to the exclusion of those records with unknown values. But considering the high number of submissions included, it may not have substantially impacted upon statistical power (Allison, 2000; Sterne et al., 2009; Steyerberg and van Veen, 2007). It was not possible to explore any biologically plausible interaction due to the characteristics of the dataset.
Missing data should be handled differently for prediction than for description or causal explanation
2020, Journal of Clinical EpidemiologyInvestigating Risk Factors and Predicting Complications in Deep Brain Stimulation Surgery with Machine Learning Algorithms
2020, World NeurosurgeryCitation Excerpt :Given the scarce nature of DBS case data and the resources required to collect it, the research team was motivated to retain as many cases as possible for analysis. Data imputation addresses this issue and various methods can be used.61-65 Four neural network regression models were developed to impute BMI for the cases with missing data.
Prognostic model for overall survival of head and neck cancer patients in the palliative phase
2024, BMC Palliative Care