HIGHLIGHTS
SUMMARY
As a result, many approaches of handling missing data, such as maximum-likelihood estimation and imputations, are preferred to listwise deletion. In the presence of missing data, likelihood function-computes separate estimates for complete and incomplete variables and the likelihoods are maximized to produce an overall estimate. To likelihood methods, imputation has been considered an effective method for managing item nonresponse bias by replacing missing data with plausible values and preserving available data and statistical power. Multivariate missing data present a challenge for imputation methods due to interdependent incomplete variables and that each incomplete . . .
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