Nonparametric Model Calibration Estimation in Survey Sampling

Montanari, Giorgio Eduardo; Ranalli, Maria Giovanna

doi:10.1198/016214505000000141

Cited by 92 publications

(44 citation statements)

References 27 publications

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“…Commonly used estimators for continuous responses are either kernel based (Kuo 1988;Kuk 1993;Dorfman and Hall 1993;Chambers et al 1993;Breidt and Opsomer 2000;Montanari and Ranalli 2005) or spline based (Little and Zheng 2004;Zheng and Little 2005;Breidt et al 2005;Opsomer et al 2007). For a recent review of such estimators in a complex survey, we refer to Breidt and Opsomer (2009).…”

Section: Introductionmentioning

confidence: 98%

Inference on finite population categorical response: nonparametric regression-based predictive approach

Adhya

Banerjee²,

Chattopadhyay

2011

AStA Adv Stat Anal

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Suppose that a finite population consists of N distinct units. Associated with the ith unit is a polychotomous response vector, d i , and a vector of auxiliary variable x i . The values x i 's are known for the entire population but d i 's are known only for the units selected in the sample. The problem is to estimate the finite population proportion vector P . One of the fundamental questions in finite population sampling is how to make use of the complete auxiliary information effectively at the estimation stage. In this article a predictive estimator is proposed which incorporates the auxiliary information at the estimation stage by invoking a superpopulation model. However, the use of such estimators is often criticized since the working superpopulation model may not be correct. To protect the predictive estimator from the possible model failure, a nonparametric regression model is considered in the superpopulation. The asymptotic properties of the proposed estimator are derived and also a bootstrapbased hybrid re-sampling method for estimating the variance of the proposed estimator is developed. Results of a simulation study are reported on the performances of the predictive estimator and its re-sampling-based variance estimator from the modelbased viewpoint. Finally, a data survey related to the opinions of 686 individuals on the cause of addiction is used for an empirical study to investigate the performance of the nonparametric predictive estimator from the design-based viewpoint.

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Section: Introductionmentioning

confidence: 98%

Inference on finite population categorical response: nonparametric regression-based predictive approach

Adhya

Banerjee²,

Chattopadhyay

2011

AStA Adv Stat Anal

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“…In the last decade, calibration estimation [7][8][9][10][11] has become an important field of research in survey sampling. Calibration is now an important methodological instrument in the production of statistics.…”

Section: Introductionmentioning

confidence: 99%

Optimum calibration points estimating distribution functions

Martínez

Rueda

Caruz

et al. 2010

Journal of Computational and Applied Mathematics

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a b s t r a c tThe calibration method has been widely discussed in the recent literature on survey sampling, and calibration estimators are routinely computed by many survey organizations. The calibration technique was introduced in [12] to estimate linear parameters as mean or total. Recently, some authors have applied the calibration technique to estimate the finite distribution function and the quantiles. The computationally simpler method in [14] is built by means of constraints that require the use of a fixed value t 0 . The precision of the resulting calibration estimator changes with the selected point t 0 . In the present paper, we study the problem of determining the optimal value t 0 that gives the best estimation under simple random sampling without replacement. A limited simulation study shows that the improvement of this optimal calibrated estimator over possible alternatives can be substantial.

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“… Calibration estimators of unistage sampling designs have been proposed by many researchers [5][6][7][8][9][10][11][12][13] , but no calibration estimator was developed for the case of multistage sampling designs which are generally used for large-to medium-scale surveys. Aditya et al…”

mentioning

confidence: 99%

District-Level Crop Yield Estimation Using Calibration Approach

et al. 2017

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Estimation of major crop yield rates at the district level using calibration estimation technique is reported here when auxiliary information is available at the unit level only for the selected villages within each district and when the sampling design under consideration is two-stage equal probability without replacement. An estimator was developed for the complex sampling design under consideration using the calibration approach. Through evaluation using real data collected from a pilot survey, we found that the proposed calibration estimator performs better than the usual design-based Horvitz-Thompson estimator under two-stage sampling design.

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Nonparametric Model Calibration Estimation in Survey Sampling

Cited by 92 publications

References 27 publications

Inference on finite population categorical response: nonparametric regression-based predictive approach

Inference on finite population categorical response: nonparametric regression-based predictive approach

Optimum calibration points estimating distribution functions

District-Level Crop Yield Estimation Using Calibration Approach

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