scholarly journals Design-Based Estimation with Record-Linked Administrative Files and a Clerical Review Sample

2018 ◽  
Vol 34 (1) ◽  
pp. 41-54
Author(s):  
Abel Dasylva
Keyword(s):  
Statistical Model ◽  
Finite Population ◽  
Probability Sample ◽  
Model Validity ◽  
Regression Estimators ◽  
Is Design ◽  
Record Pair

Abstract This article looks at the estimation of an association parameter between two variables in a finite population, when the variables are separately recorded in two population registers that are also imperfectly linked. The main problem is the occurrence of linkage errors that include bad links and missing links. A methodology is proposed when clerical-reviews may reliably determine the match status of a record-pair, for example using names, demographic and address information. It features clerical-reviews on a probability sample of pairs and regression estimators that are assisted by a statistical model of comparison outcomes in a pair. Like other regression estimators, this estimator is design-consistent regardless of the model validity. It is also more efficient when the model holds.

scholarly journals Some Median Type Estimators to Estimate the Finite Population Mean

2020 ◽  
pp. 48-58
Author(s):  
Waqar Hafeez ◽  
Javid Shabbir ◽  
Muhammad Taqi Shah ◽  
Shakeel Ahmed
Keyword(s):  
Linear Regression ◽  
Finite Population ◽  
Auxiliary Variable ◽  
Maximum Efficiency ◽  
Order Of Approximation ◽  
Study Variable ◽  
Sample Mean ◽  
First Order ◽  
Regression Estimators ◽  
Class Of Estimators

Researchers always appreciates estimators of finite population quantities, especially mean, with maximum efficiency for reaching to valid statistical inference.  Apart from ratio, product and regression estimators, exponential estimators are widely considered by survey statisticians. Motivated from the idea of exponential type estimators, in this article, we propose some new estimators utilizing known median of the study variable with mean of auxiliary variable. Theoretical properties of the suggested estimators are studied up to first order of approximation. In addition, an empirical and simulation study the comparison of median based proposed class of estimators with sample mean, ratio and linear regression estimators  are discussed. The results expose that the proposed estimators are more efficient than the existing estimators.

scholarly journals Integration of Nonprobability and Probability Samples via Survey Weights

2021 ◽  
Vol 10 (6) ◽  
pp. 5
Author(s):  
Balgobin Nandram ◽  
Jai Won Choi ◽  
Yang Liu
Keyword(s):  
Population Model ◽  
Finite Population ◽  
Percent Level ◽  
Small Sample ◽  
Sample Survey ◽  
Alternative Methods ◽  
Population Means ◽  
Probability Sample ◽  
Two Samples ◽  
The Cost

Probability sample encounters the problems of increasing cost and nonresponse. The cost has rapidly been increasing in executing a large probability sample survey, and, for some surveys, response rate can be below the 10 percent level. Therefore, statisticians seek some alternative methods. One of them is to use a large nonprobability sample (S_1 ) supplemented by a small probability sample (S_2 ). Both samples are taken from the same population and they include common covariates, and a third sample (S_3 ) is created by combining these two samples; S_1  can be biased and S_2  may have large sample variance. These two problems are reduced by survey weights and combining the two samples. Although S_2  is a small sample, it provides good properties of unbiasedness in estimation and of survey weights. With these known weights, we obtain adjusted sample weights (ASW), and create a sample model from a finite population model. We fit the sample model to obtain its parameters and generate values from the population model. Similarly, we repeat these processes for other two samples, S_1  and S_3  and for different statistical methods. We show reduced biases of the finite population means and reduced variances.as the combined sample size becomes large. We analyze sample data to show the reduction of these two errors.

Predictive Estimation of Finite Population Variance

1998 ◽  
Vol 48 (3-4) ◽  
pp. 229-236 ◽  
Author(s):  
R.S. Biradar ◽  
H.P. Singh
Keyword(s):  
Finite Population ◽  
Auxiliary Information ◽  
The Other ◽  
Mean Square ◽  
Population Variance ◽  
Asymptotic Expressions ◽  
Regression Estimators ◽  
Predictive Approach ◽  
Variance Formula ◽  
Mean And Variance

Adopting predictive approach, estimators are proposed for population variance [Formula: see text] using different predictors for mean and variance of unobserved units in the population. Asymptotic expressions for bias and mean square error of these new estimators are obtained and compared with those of some known estimators of population variance. Predictive character of some known estimators is also examined . An empirical study demonstrated superiority over others of one of the proposed estimators, which uses regression estimators as predictors for mean and variance of unobserved units. Also, one of the other proposed estimators which does not utilize any auxiliary information has been found to be more efficient than the traditional unbiased estimator [Formula: see text].

scholarly journals Some Improved Ratio, Product, and Regression Estimators of Finite Population Mean When Using Minimum and Maximum Values

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Manzoor Khan ◽  
Javid Shabbir
Keyword(s):  
Finite Population ◽  
Auxiliary Information ◽  
Efficient Estimation ◽  
Order Of Approximation ◽  
Population Mean ◽  
Mean Squared Errors ◽  
First Order ◽  
Regression Estimators ◽  
Improved Performance

Efficient estimation of finite population mean is carried out by using the auxiliary information meaningfully. In this paper we have suggested some modified ratio, product, and regression type estimators when using minimum and maximum values. Expressions for biases and mean squared errors of the suggested estimators have been derived up to the first order of approximation. The performances of the suggested estimators, relative to their usual counterparts, have been studied, and improved performance has been established. The improvement in efficiency by making use of maximum and minimum values has been verified numerically.

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