Research paper | 30-October-2017
estimation variable and the auxiliary variables employed in the calibration. The JCE achieves better performance when the auxiliary variables can fully explain the variability in the study variables or at least when the auxiliary variables are strong correlates of the estimation variables. As opposed to the standard dual frame estimators, the JCE does not require domain membership information. Even if included in the JCE auxiliary variables, the effect of the randomly misclassified domains does not
Mahmoud A. Elkasabi,
Steven G. Heeringa,
James M. Lepkowski
Statistics in Transition New Series, Volume 16 , ISSUE 1, 7–36
Sampling Methods | 26-May-2018
The present paper emphasizes the role of two auxiliary variables on both the occasions to improve the precision of estimates at the current (second) occasion in two-occasion successive sampling. Information on two auxiliary variables, which are positively correlated with the study variable, has been used with the aid of exponential type structures and an efficient estimation procedure of population mean on the current (second) occasion has been suggested. The behaviour of the proposed estimator
Jaishree Prabha Karna,
Dilip Chandra Nath
Statistics in Transition New Series, Volume 19 , ISSUE 1, 25–44
Sampling Methods | 22-July-2018
In this article, we propose a class of generalized exponential type estimators to estimate the finite population mean by using two auxiliary variables under non-response in simple random sampling. The proposed estimator under non-response in different situations has been studied and gives minimum mean square error as compared to all other considered estimators. Usual exponential ratio type estimator, exponential product type estimator and many more estimators are also identified from the
Siraj Muneer,
Javid Shabbir,
Alamgir Khalil
Statistics in Transition New Series, Volume 19 , ISSUE 2, 259–276
Sampling Methods | 27-May-2018
This paper examines the chain of weights, beginning with the basic sampling weights for the respondents. These were then converted to reweights to reduce the bias due to missing quantities. If micro auxiliary variables are available for a gross sample, we suggest taking advantage first of the response propensity weights, and then of the calibrated weights with macro (aggregate) auxiliary variables. We also examined the calibration methodology that starts from the basic weights. Simulated data
Seppo Laaksonen,
Auli Hämäläinen
Statistics in Transition New Series, Volume 19 , ISSUE 1, 45–60
Research Article | 13-December-2018
information many authors have formulated the problem as a MPP by redefining the problem as the problem of optimum strata width, and developed a solution procedure using dynamic programming technique. By using many distributions they worked out the optimum strata boundary points for the population under different allocation. In this paper, under proportional allocation OSBs are determined for the study variable using two auxiliary variables as the basis of stratification with uniform, right-triangular
Faizan Danish
Statistics in Transition New Series, Volume 19 , ISSUE 3, 507–526
Research Article | 18-March-2020
Rohini Yadav,
Rajesh Tailor
Statistics in Transition New Series, Volume 21 , ISSUE 1, 1–12
Article | 06-July-2017
Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A
Andreea L. Erciulescu,
Wayne A. Fuller
Statistics in Transition New Series, Volume 17 , ISSUE 1, 9–24
Article | 20-December-2020
Continuous distribution of variables under study and auxiliary variables are considered. The purpose of the paper is to estimate the mean of the variable under study using a sampling design which is dependent on the observation of a continuous auxiliary variable in the whole population. Auxiliary variable values observed in this population allow to estimate the inclusion density function of the sampling design. The variance of the continuous version of the Horvitz-Thompson estimator under the
Janusz L. Wywiał
Statistics in Transition New Series, Volume 21 , ISSUE 5, 1–16
Article | 15-March-2019
In this paper, an investigation has been carried out to deal with a unified approach of estimation procedures of population variance in two-phase sampling design under missing at random non-response mechanism circumstances. Using two auxiliary variables, we have developed different chain-type exponential estimators of finite population variance for two different set-ups and studied their properties under the different assumption of random non-response considered by Tracy and Osahan (1994). The
G. N. Singh,
Amod Kumar,
Gajendra K. Vishwakarma
Statistics in Transition New Series, Volume 19 , ISSUE 4, 575–596
Article | 15-September-2020
Small domain estimation covers a set of statistical methods for estimating quantities in domains not previously considered by the sample design. In such cases, the use of a model-based approach that relates sample estimates to auxiliary variables is indicated. In this paper, we propose and evaluate skew normal small area time models for the Brazilian Annual Service Sector Survey (BASSS), carried out by the Brazilian Institute of Geography and Statistics (IBGE). The BASSS sampling plan cannot
André Felipe Azevedo Neves,
Denise Britz do Nascimento Silva,
Fernando Antônio da Silva Moura
Statistics in Transition New Series, Volume 21 , ISSUE 4, 84–102
Article | 18-March-2020
, especially in domains where samples are of small sizes. These alternative models are supplied with auxiliary variables. The study seeks to present the characteristics of and differences among small business units cross-classified by selected NACE sections and district units of the provinces of Mazowieckie and Wielkopolskie. It was carried out on the basis of data from a survey conducted by the Statistical Office in Poznan and from administrative registers. It is the first study which attempts to
Grażyna Dehnel,
Łukasz Wawrowski
Statistics in Transition New Series, Volume 21 , ISSUE 1, 137–157
Article | 24-August-2017
important reasons are weighting for unequal probability of selection, compensation for nonresponse, and post-stratification. Many highly efficient estimation methods in survey sampling require strong information about auxiliary variables, x. The most common estimation methods using auxiliary information in estimation stage are regression and ratio estimator. This paper proposes a sequential data weighting procedure for the estimators of combined ratio mean in complex sample surveys and general variance
Aylin Alkaya,
H. Öztaş Ayhan,
Alptekin Esin
Statistics in Transition New Series, Volume 18 , ISSUE 2, 247–270
Research Article | 18-March-2020
prediction of finite population totals, see Eideh (2016). The derived parametric predictors of T use the observation for the response set of the study variable or variable of interest, values of auxiliary variables and their population totals, sampling weights, and propensity scores. An interesting outcome of the T study is that most predictors known from model-based survey sampling can be derived as a special case from this general theory, see Chambers and Clark (2012).
Abdulhakeem Eideh
Statistics in Transition New Series, Volume 21 , ISSUE 1, 13–35