scholarly journals A Generalized Two Phase Sampling Estimator of Ratio of Population Means Using Auxiliary Information

2021 ◽  
Author(s):  
Tarunpreet Kaur Ahuja ◽  
Peeyush Misra ◽  
O. K. Belwal
Keyword(s):  
Mean Squared Error ◽  
Auxiliary Information ◽  
Two Phase ◽  
Population Means ◽  
Minimum Mean Squared Error ◽  
Second Moments ◽  
Squared Error ◽  
Phase Sampling ◽  
Theoretical Results ◽  
Two Phase Sampling

This paper addresses the problem of estimating ratio of two population means by using quantitative auxiliary knowledge in the form of first and second moments. Through this paper, an improved generalized two phase sampling estimator has been proposed. The relative bias and mean squared error of the suggested estimator has been derived and studied. Also, a comparative study with the conventional estimators has been included to establish its superiority. Besides theoretical comparisons, a subset of optimum estimators having the same minimum mean squared error (MSE) is also explored. An empirical study is also carried out to support theoretical results.

A Class of Estimators for a Finite Population Mean Based on Multivariate Information and General two Phase Sampling

1995 ◽  
Vol 45 (3-4) ◽  
pp. 203-218 ◽  
Author(s):  
T. P. Tripathi ◽  
M. S. Ahmed
Keyword(s):  
Finite Population ◽  
Population Data ◽  
Two Phase ◽  
Population Means ◽  
Population Mean ◽  
Phase Sampling ◽  
Optimum Estimator ◽  
Class Of Estimators ◽  
Relative Gains ◽  
Two Phase Sampling

A class of estimators for a finite population mean is presented for the situations where population means of some auxiliary variables are known while those of others are unknown. The results for general two phase sampling are indicated while the detailed discussion is made for the case when SRSWOR is used at both the phases. While several known estimators belong to the proposed clas~ some new estimators are identified as well. The optimum estimator in the proposed class is found to be better than the so-called chain ratio and regression estimators discu ssed by Chand (1975). Kiregyera (1984) and Mukerjee et al. (1987). The relative gains in efficiency of tho proposed optimum estimator over the others are obtained for a natural population data and found to be quite appreciable.

New regression estimators in forest inventories with two-phase sampling and partially exhaustive information: a design-based Monte Carlo approach with applications to small-area estimation

2013 ◽  
Vol 43 (11) ◽  
pp. 1023-1031 ◽  
Author(s):  
Daniel Mandallaz ◽  
Jochen Breschan ◽  
Andreas Hill
Keyword(s):  
Auxiliary Information ◽  
Cluster Sampling ◽  
Lidar Data ◽  
Second Phase ◽  
Regression Estimator ◽  
Two Phase ◽  
Sampling Schemes ◽  
Forest Inventories ◽  
Phase Sampling ◽  
Two Phase Sampling

We consider two-phase sampling schemes where one component of the auxiliary information is known in every point (“wall-to-wall”) and a second component is available only in the large sample of the first phase, whereas the second phase yields a subsample with the terrestrial inventory. This setup is of growing interest in forest inventory thanks to the recent advances in remote sensing, in particular, the availability of LiDAR data. We propose a new two-phase regression estimator for global and local estimation and derive its asymptotic design-based variance. The new estimator performs better than the classical regression estimator. Furthermore, it can be generalized to cluster sampling and two-stage tree sampling within plots. Simulations and a case study with LiDAR data illustrate the theory.

scholarly journals Improved Exponential Dual to Ratio Type Imputation for Missing Data under Two-Phase Sampling

2021 ◽  
Vol 9 (8) ◽  
pp. 2338-2348
Author(s):  
B. K. Singh
Keyword(s):  
Missing Data ◽  
Mean Squared Error ◽  
Numerical Study ◽  
Two Phase ◽  
Large Sample Approximation ◽  
Phase Sampling ◽  
Point Estimator ◽  
Sample Approximation ◽  
Two Populations ◽  
Two Phase Sampling

Abstract: In this paper, authors have proposed a class of exponential dual to ratio type compromised imputation technique and corresponding point estimator in two-phase sampling design. Two different sampling designs in two-phase sampling are compared under imputed data. The bias and M.S.E. of suggested estimator is derived in the form of population parameters using the concept of large sample approximation. Numerical study is performed over two populations using the expressions of bias and M.S.E. and efficiency compared with existing estimators. Keywords: Missing data, Bias, Mean squared error (M.S.E), Two-phase sampling, SRSWOR, Compromised Imputation (C.I.).

scholarly journals Some Improved Estimators of Population Mean using Two-Phase Sampling Scheme in the Presence of Non-Response

2021 ◽  
pp. 911-919
Author(s):  
Manoj Kumar Chaudhary ◽  
Amit Kumar ◽  
Gautam K. Vishwakarma
Keyword(s):  
Auxiliary Variable ◽  
Study Variable ◽  
Two Phase ◽  
Population Mean ◽  
Usual Estimator ◽  
Phase Sampling ◽  
Improved Estimators ◽  
Mean Square Errors ◽  
Theoretical Results ◽  
Two Phase Sampling

In the present paper, we have proposed some improved estimators of the population mean utilizing the information on two auxiliary variables adopting the idea of two-phase sampling under non-response. In order to propose the estimators, we have assumed that the study variable and first auxiliary variable suffer from non-response while the second (additional) auxiliary variable is free from non-response. We have derived the expressions for biases and mean square errors of the proposed estimators and compared them with that of usual estimator and some well known existing estimators of the population mean. The theoretical results have also been illustrated with some empirical data.

scholarly journals A combination sampling approach for epidemiologic research in humanitarian settings: a case analysis of a study of depressive disorder prevalence among refugees in Greece

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Danielle N. Poole ◽  
Nathaniel A. Raymond ◽  
Jos Berens ◽  
Mark Latonero ◽  
Julie Ricard ◽  
...  
Keyword(s):  
Depressive Disorder ◽  
Case Analysis ◽  
Refugee Camp ◽  
Second Phase ◽  
Two Phase ◽  
Humanitarian Emergencies ◽  
Prevention And Treatment ◽  
Phase Sampling ◽  
Two Phase Sampling ◽  
Sampling Approach

Abstract Background Understanding the burden of common mental health disorders, such as depressive disorder, is the first step in strengthening prevention and treatment in humanitarian emergencies. However, simple random sampling methods may lead to a high risk of coercion in settings characterized by a lack of distinction between researchers and aid organizations, mistrust, privacy concerns, and the overarching power differential between researchers and populations affected by crises. This case analysis describes a sampling approach developed for a survey study of depressive disorder in a Syrian refugee camp in Greece (n = 135). Discussion Syrian refugees face an extraordinarily high burden of depressive disorder during the asylum process (43%), necessitating population screening, prevention, and treatment. In order to preserve the informed consent process in this refugee camp setting, the research team developed a two-phase sampling strategy using a map depicting the geographical layout of the housing units within the camp. In the first phase, camp management announced a research study was being undertaken and individuals were invited to volunteer to participate. The participants’ container (housing) numbers were recorded on the map, but were not linked to the survey data. Then, in the second phase, the camp map was used for complementary sampling to reach a sample sufficient for statistical analysis. As a result of the two phases of the sampling exercise, all eligible adults from half the containers in each block were recruited, producing a systematic, age- and sex-representative sample. Conclusions Combining sampling procedures in humanitarian emergencies can reduce the risk of coerced consent and bias by allowing participants to approach researchers in the first phase, with a second phase of sampling conducted to recruit a systematic sample. This case analysis illuminates the feasibility of a two-phase sampling approach for drawing a quasi-random, representative sample in a refugee camp setting.

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