Two-step calibration of design weights under two auxiliary variables in sample survey

2019 ◽  
Vol 89 (12) ◽  
pp. 2316-2327 ◽  
Author(s):  
Alka ◽  
Piyush Kant Rai ◽  
Muhammad Qasim
Keyword(s):  
Sample Survey ◽  
Auxiliary Variables ◽  
Design Weights

scholarly journals Use of Auxiliary Variables and Asymptotically Optimum Estimators in Double Sampling

2016 ◽  
Vol 5 (3) ◽  
pp. 55 ◽  
Author(s):  
M. E. Kanwai ◽  
O. E. Asiribo ◽  
A. Isah
Keyword(s):  
Mean Squared Error ◽  
Population Level ◽  
Auxiliary Variable ◽  
Sample Survey ◽  
Comparative Approach ◽  
Double Sampling ◽  
Auxiliary Variables ◽  
Two Phase ◽  
Optimum Estimator ◽  
The Mean

This paper explore the need for exploiting auxiliary variables in sample survey and utilizing asymptotically optimum estimator in double sampling to increase the efficiency of estimators. The study proposed two types of estimators with two auxiliary variables for two phase sampling when there is no information about auxiliary variables at population level. The expressions for the Mean Squared Error (MSE) of the proposed estimators were derived to the first order of approximation. An empirical comparative approach of the minimum variances and percent relative efficiency were adopted to study the efficiency of the proposed and existing estimators. It was established that, the proposed estimators performed more efficiently than the mean per unit estimator and other previous estimators that don’t use auxiliary variable and that are not asymptotically optimum. Also, it was established that estimators that are asymptotically optimum that utilized single auxiliary variable are more efficient than those that are not asymptotically optimum with two auxiliary variables.

A balanced sampling and calibration

2016 ◽  
Vol 61 (3) ◽  
pp. 38-60
Author(s):  
Arkadiusz Kozłowski
Keyword(s):  
Sampling Design ◽  
The Other ◽  
General Idea ◽  
Auxiliary Variables ◽  
Numerical Examples ◽  
Balanced Sampling ◽  
Other Hand ◽  
Design Weights

A balanced sampling design is a design in which Horvitz-Thompson estimators of population totals for a set of auxiliary variables equal the known totals of these variables. On the other hand, calibration is a technique where the modification of design weights occurs in such a way that the new weights, when applied to auxiliary variables, reproduce, i.e. estimate withouterror, the known totals for these variables. The general idea behind balanced sampling and calibration is thus the same — both techniques tend to reproduce known totals of the auxiliary variables. The purpose of the paper is to describe and compare both techniques, considering them as alternatives in achieving the same goal. More attention was devoted to balanced sampling. The algorithm for selecting a sample was illustrated with two numerical examples. The comparison between balanced sampling and calibration, as alternatives, indicates calibration, but the best strategy is to use both methods simultaneously.

Looking for optimal auxiliary variables in sample survey quantile estimation

Statistics ◽  
2007 ◽  
Vol 41 (3) ◽  
pp. 241-252 ◽  
Author(s):  
M. D. Martínez-Miranda ◽  
M. Rueda ◽  
A. Arcos
Keyword(s):  
Quantile Estimation ◽  
Sample Survey ◽  
Auxiliary Variables

scholarly journals Weighting Procedure of the Austrian Microcensus using Administrative Data

2016 ◽  
Vol 45 (3) ◽  
pp. 3-14
Author(s):  
Angelika Meraner ◽  
Daniela Gumprecht ◽  
Alexander Kowarik
Keyword(s):  
Sample Size ◽  
Administrative Data ◽  
Sample Survey ◽  
Sampling Unit ◽  
Primary Sampling Unit ◽  
New Approach ◽  
Cluster Sample ◽  
Additional Dimension ◽  
Austrian Population ◽  
Design Weights

The Austrian microcensus is the biggest sample survey of the Austrian population, itis a regionally stratied cluster sample with a rotational pattern. The sampling fractionsdier signicantly between the regions, therefore the sample size of the regions is quitehomogeneous. The primary sampling unit is the household, within each household allpersons are surveyed. The design weights are the input for the calibration on populationcounts and household forecasts. It is performed by iterative proportional tting. Untilthe third quarter of 2014 only demographic, regional and household information wereused in the weighting procedure. From the fourth quarter 2014 onwards the weightingprocess was improved by adding an additional dimension to the calibration, namely alabour status generated from administrative data and available for the whole population.Apart from that some further minor changes were introduced. This paper describes themethodological and practical issues of the microcensus weighting process and the varianceestimation applied from 2015 onwards. The new procedure was used for the rst timefor the forth quarter of 2014, published at the end of March 2015. At the same time, allprevious microcensus surveys back to 2004 were reweighted according to the new approach.

scholarly journals An Appraisal of Common Reweighting Methods for Nonresponse in Household Surveys Based on the Norwegian Labour Force Survey and the Statistics on Income and Living Conditions Survey

2020 ◽  
Vol 36 (1) ◽  
pp. 151-172
Author(s):  
Nancy Duong Nguyen ◽  
Li-Chun Zhang
Keyword(s):  
Data Collection ◽  
Labour Force ◽  
Real Data ◽  
Household Surveys ◽  
Labour Force Survey ◽  
Simulation Studies ◽  
Statistical System ◽  
Auxiliary Variables ◽  
Statistical Adjustment ◽  
Design Weights

AbstractDespite increasing efforts during data collection, nonresponse remains sizeable in many household surveys. Statistical adjustment is hence unavoidable. By reweighting the design, weights of the respondents are adjusted to compensate for nonresponse. However, there is no consensus on how this should be carried out in general. Theoretical comparisons are inconclusive in the literature, and the associated simulation studies involve hypothetical situations not all equally relevant to reality. In this article we evaluate the three most common reweighting approaches in practice, based on real data in Norway from the two largest household surveys in the European Statistical System. We demonstrate how cross- examination of various reweighting estimators can help inform the effectiveness of the available auxiliary variables and the choice of the weight adjustment method.

On the Causes of Socio-Economic Inequality Reproduction: What Does Resources Approach Show?

2014 ◽  
pp. 144-160
Author(s):  
E. Avraamova ◽  
T. Maleva
Keyword(s):  
Social Dynamics ◽  
Economic Inequality ◽  
Poverty Rate ◽  
Economic Behavior ◽  
Sample Survey ◽  
Family Welfare ◽  
Rate Reduction ◽  
Rational Models ◽  
Information Database ◽  
Vertical Mobility

This paper presents an attempt at answering the question of why the scope of socio-economic inequality stays the same in Russia despite the poverty rate reduction. The authors are looking for the causes of this phenomenon in the domain of social dynamics, i.e., in the nature of current vertical mobility mechanisms. To study these mechanisms the authors use resources approach. The information database of the research is the representative sample survey carried by the Institute for Social Analysis and Forecasting at RANEPA in 2013. The majority of the respondents have, in fact, vague idea of general parameters of the economic development of the country and of their personal prospects to adapt to possible changes. This state of things hinders the development of rational models of socio-economic behavior directed towards the growth of personal and family welfare and productive in terms of national economy development - these, eventually, would advance the reduction of socio-economic inequality. Various groups of population are predominantly oriented towards converting social capital viewed not in terms of trust and solidarity, but in terms of ties or connections and of personal loyalty.

Use of Collaborative Technologies for Knowledge Management in Psychiatric Hospitals in Southwest Nigeria

Mousaion ◽  
2019 ◽  
Vol 37 (3) ◽  
Author(s):  
Oluyemi Folorunso Ayanbode ◽  
Williams Ezinwa Nwagwu
Keyword(s):  
Knowledge Management ◽  
Psychiatric Hospitals ◽  
Task Interdependence ◽  
Sample Survey ◽  
Team Members ◽  
Collaborative Technologies ◽  
Southwest Nigeria ◽  
Transfer And Retention ◽  
Retention Of Knowledge ◽  
Therapy Team

This article concerns the study examining the use of collaborative technologies (CTs) for the acquisition, creation, sharing, transfer, and retention of knowledge by therapy team members (TTMs) in psychiatric hospitals, and the determinants of the use of CTs as well as how they relate to knowledge management (KM) practices. The skills of the TTMs in the use of CTs were also investigated. Carried out within the positivist and constructivist paradigms, a sample survey was conducted among TTMs from two purposively selected psychiatric hospitals in Southwest Nigeria. Quantitative data was collected from self-administered questionnaires completed by 283 TTMs and was analysed using the Statistical Package for Social Sciences (SPSS) 22. Qualitative data was collected from interviews conducted with four heads of departments. The study showed that the TTMs in the relevant hospitals used 26 different CTs for knowledge acquisition, creation, sharing, transfer, and retention. The largest proportion (84.5%) of the respondents confirmed that skill in the use of CTs determined the use of CTs for KM practices. More than half (54.3%) of the TTMs were highly skilled in the use of CTs for KM practices. The findings suggested that the respondents were positively inclined towards the use of CTs and that they were involved in the use of various CTs to facilitate KM practices and processes. It was found that task interdependence was characteristic of the TTMs’ work in the selected psychiatric hospitals, and that, to benefit from the potential advantages of task interdependence and to effectively employ CTs in operations and processes, TTMs’ skills in the use of CTs should be developed. In addition, professional ties among experts in different fields of specialisation should be encouraged.

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