Imputation of individual values of a variable using product predictors
Abstract:
Missing data is a common problem present in almost every data collection. It is particularly important in sample survey research. The existence of missing observations (non-response) is solved in many sample surveys using some technique of imputation. They permit replacing the missing data. Several imputation techniques have been developed in the specialized literature. The capacity of them for predicting the mean or a total is the token for their evaluation. This paper presents an imputation rule with the main goal of predicting individual values. An auxiliary variable X is known for all the units and a product type predictor is developed for predicting the value of variable of interest in each non-respondent. The unbiasedness of the predictions is derived and the Mean Squared Errors (MSE`s). Some conclusions are pointed out.
Año de publicación:
2021
Keywords:
- Missing data
- Unbiasedness mean squared errors
- Product type pbkp_redictor
- imputation
Fuente:
scopusTipo de documento:
Article
Estado:
Acceso restringido
Áreas de conocimiento:
Áreas temáticas de Dewey:
- Programación informática, programas, datos, seguridad
Objetivos de Desarrollo Sostenible:
- ODS 17: Alianzas para lograr los objetivos
- ODS 8: Trabajo decente y crecimiento económico
- ODS 9: Industria, innovación e infraestructura