A robust imputation method for missing responses and covariates in sample selection models
Sample selection arises when the outcome of interest is partially observed in a study. Although sophisticated statistical methods in the parametric and non-parametric framework have been proposed to solve this problem, it is yet unclear how to deal with selectively missing covariate data using simpl...
Główni autorzy: | Ogundimu, E, Collins, G |
---|---|
Format: | Journal article |
Język: | English |
Wydane: |
SAGE Publications
2017
|
Podobne zapisy
-
Imputation of Missing Clinical Covariates for Downstream Classification Problems
od: Benjamin Agbo, i wsp.
Wydane: (2023-01-01) -
On the Relation between Prediction and Imputation Accuracy under Missing Covariates
od: Burim Ramosaj, i wsp.
Wydane: (2022-03-01) -
Multiple imputation of missing covariates with non-linear effects and interactions: an evaluation of statistical methods
od: Seaman Shaun R, i wsp.
Wydane: (2012-04-01) -
Robust regression imputation for analyzing missing data
od: Rana, Md. Sohel, i wsp.
Wydane: (2012) -
Robust Random Regression Imputation method for missing data in the presence of outliers
od: John, Ahamefule Happy
Wydane: (2013)