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Estimation of logistic regression parameters for complex survey data: simulation study based on real survey data - RP:5396

Autor según el artículo:Arostegui, Inmaculada
Aramendi, Jorge
Barrio, Irantzu
Iparragirre, Amaia
Año de publicación de la revista:2024
Tipo de publicación:info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
Resumen:In complex survey data, each sampled observation has assigned a sampling weight, indicating the number of units that it represents in the population. Whether sampling weights should or not be considered in the estimation process of model parameters is a question that still continues to generate much discussion among researchers in different fields. We aim to contribute to this debate by means of a real data based simulation study in the framework of logistic regression models. In order to study their performance, three methods have been considered for estimating the coefficients of the logistic regression model: a) the unweighted model, b) the weighted model, and c) the unweighted mixed model. The results suggest the use of the weighted logistic regression model is superior, showing the importance of using sampling weights in the estimation of the model parameters.
Palabras clave:complex survey data
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