This paper deals with the nonresponse problem in the estimation of the mean of a finite population following a nonparametric approach. Weigthing adjustment is a popular method for Handling unit nonresponse. it operates by increasing the sampling weigths of the respondents in the sampleusing estimates of their respond probabilities. Typically these estimates are obtained by fitting parametric models relating response occurrence and auxiliary variables. An alternative solution is the nonparametric estimation of the response probabilities. The aim of this paper is to investigate, via simulation exsperiments, the small-sample properties of kernel regression estimates of the response probabilities whrn the auxiliary information consists in a mix of continuous and discrete variables. Furthermore the practical behaviour of the method is evaluated on data of a web survey on accomodation facilities in the province of Florence.
Kernel-Type Smoothing Methods of Adjusting for Unit Nonresponse in Presence of Multiple and Different Type Covariates / E. Rocco. - STAMPA. - (2011), pp. 135-142. [10.1007/978-3-642-11363-5_16]
Kernel-Type Smoothing Methods of Adjusting for Unit Nonresponse in Presence of Multiple and Different Type Covariates
ROCCO, EMILIA
2011
Abstract
This paper deals with the nonresponse problem in the estimation of the mean of a finite population following a nonparametric approach. Weigthing adjustment is a popular method for Handling unit nonresponse. it operates by increasing the sampling weigths of the respondents in the sampleusing estimates of their respond probabilities. Typically these estimates are obtained by fitting parametric models relating response occurrence and auxiliary variables. An alternative solution is the nonparametric estimation of the response probabilities. The aim of this paper is to investigate, via simulation exsperiments, the small-sample properties of kernel regression estimates of the response probabilities whrn the auxiliary information consists in a mix of continuous and discrete variables. Furthermore the practical behaviour of the method is evaluated on data of a web survey on accomodation facilities in the province of Florence.File | Dimensione | Formato | |
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