scholarly journals Estimating a Finite Population Mean under Random Non-Response in Two Stage Cluster Sampling with Replacement

2017 ◽  
Vol 07 (05) ◽  
pp. 834-848 ◽  
Author(s):  
Nelson Kiprono Bii ◽  
Christopher Ouma Onyango ◽  
John Odhiambo
Keyword(s):  
Finite Population ◽  
Cluster Sampling ◽  
Two Stage ◽  
Population Mean

Some calibration estimators for finite population mean in two-stage stratified random sampling

2019 ◽  
Vol 49 (17) ◽  
pp. 4234-4247
Author(s):  
Dhirendra Singh ◽  
Bhupendra Veer Singh Sisodia ◽  
Nidhi ◽  
Sandeep Pundir
Keyword(s):  
Random Sampling ◽  
Finite Population ◽  
Stratified Random Sampling ◽  
Two Stage ◽  
Population Mean

scholarly journals Boundary Bias Correction Using Weighting Method in Presence of Nonresponse in Two-Stage Cluster Sampling

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Nelson Kiprono Bii ◽  
Christopher Ouma Onyango ◽  
John Odhiambo
Keyword(s):  
Bias Correction ◽  
Finite Population ◽  
Asymptotic Properties ◽  
Kernel Density ◽  
Boundary Effects ◽  
Cluster Sampling ◽  
Weighting Method ◽  
Population Mean ◽  
Bias Variance ◽  
Boundary Bias

Kernel density estimators due to boundary effects are often not consistent when estimating a density near a finite endpoint of the support of the density to be estimated. To address this, researchers have proposed the application of an optimal bandwidth to balance the bias-variance trade-off in estimation of a finite population mean. This, however, does not eliminate the boundary bias. In this paper weighting method of compensating for nonresponse is proposed. Asymptotic properties of the proposed estimator of the population mean are derived. Under mild assumptions, the estimator is shown to be asymptotically consistent.

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