Estimating the proportion of a categorical variable with probit regression
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URI: http://hdl.handle.net/10835/14878
ISSN: 0049-1241
DOI: https://doi.org/10.1177/0049124118761771
ISSN: 0049-1241
DOI: https://doi.org/10.1177/0049124118761771
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Martínez Puertas, Sergio; Arcos Cebrián, Antonio; Rueda García, María del Mar; Martínez Puertas, HelenaDate
2018-03-08Abstract
This paper discusses the estimation of a population proportion, using the auxiliary information available, which is incorporated into the estimation procedure by a probit model fit. Three probit regression estimators are considered, using model-based and model-assisted approaches. The theoretical properties of the proposed estimators are derived and discussed. Monte Carlo experiments were carried out for simulated data and for real data taken from a database of confirmed dengue cases in Mexico. The probit estimates gives valuable results in comparison to alternative estimators. Finally, the proposed methodology is applied to data obtained from an immigration survey.
Palabra/s clave
Auxiliary information
Calibration estimator
Probit Regression
Fi- nite population
Sampling design