Currently, missing data is handled by simply removing affected observations. However, there may be more effective approaches that preserve more information while maintaining statistical validity.
Deng et al. (2018), Section 5 discusses alternative methods that might be worth considering. Would it be possible to explore these approaches to improve missing data handling?
Currently, missing data is handled by simply removing affected observations. However, there may be more effective approaches that preserve more information while maintaining statistical validity.
Deng et al. (2018), Section 5 discusses alternative methods that might be worth considering. Would it be possible to explore these approaches to improve missing data handling?