Nonparametric estimation of response probabilities in sampling theory

Research output: Contribution to journalArticle

Abstract

We deal with the nonresponse problem by drawing on the model of selection in phases that was proposed by Sarndal and Swenson (1987). To estimate response probabilities, we use the nonparametric approach first advanced by Giommi (1987). We define estimators according to the nonparametric estimation (NPE) model, and we study their general properties empirically. Inference is based on the concept of quasi-randomization (Oh and Scheuren 1983). The emphasis is on estimating the variance and constructing confidence intervals. We find, by way of a Monte Carlo study, that it is possible to improve the quality of the estimators considered by using a variant of the NPE approach. The latter also serves to confirm the performance of regression estimators in terms of variance estimation.
Original languageEnglish
Pages (from-to)177-184
Number of pages8
JournalSurvey Methodology
Volume20
Issue number2
Publication statusPublished - 1994
Externally publishedYes

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Sampling Theory
Nonparametric Estimation
Sampling
Estimator
Non-response
Variance Estimation
Regression Estimator
Monte Carlo Study
Randomisation
Confidence interval
Model
Estimate
Concepts
Drawing

Cite this

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abstract = "We deal with the nonresponse problem by drawing on the model of selection in phases that was proposed by Sarndal and Swenson (1987). To estimate response probabilities, we use the nonparametric approach first advanced by Giommi (1987). We define estimators according to the nonparametric estimation (NPE) model, and we study their general properties empirically. Inference is based on the concept of quasi-randomization (Oh and Scheuren 1983). The emphasis is on estimating the variance and constructing confidence intervals. We find, by way of a Monte Carlo study, that it is possible to improve the quality of the estimators considered by using a variant of the NPE approach. The latter also serves to confirm the performance of regression estimators in terms of variance estimation.",
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Nonparametric estimation of response probabilities in sampling theory. / NIYONSENGA, Theo.

In: Survey Methodology, Vol. 20, No. 2, 1994, p. 177-184.

Research output: Contribution to journalArticle

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AB - We deal with the nonresponse problem by drawing on the model of selection in phases that was proposed by Sarndal and Swenson (1987). To estimate response probabilities, we use the nonparametric approach first advanced by Giommi (1987). We define estimators according to the nonparametric estimation (NPE) model, and we study their general properties empirically. Inference is based on the concept of quasi-randomization (Oh and Scheuren 1983). The emphasis is on estimating the variance and constructing confidence intervals. We find, by way of a Monte Carlo study, that it is possible to improve the quality of the estimators considered by using a variant of the NPE approach. The latter also serves to confirm the performance of regression estimators in terms of variance estimation.

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