Parametric models for response errors in survey sampling (original) (raw)

Fundamentals of Survey Sampling

Since the beginning of the twentieth century the economic and social life of the people and the functional system of industry and business, educational and medical facilities and other activities of the community have undergone substantial changes due to spectacular developments in the field of science and technology. Now the emphasis is on specialization in mass production and utilization of goods and services of a given type with a view to get the maximum possible benefit per unit of cost. Considerable planning is required in a large-scale projects and any rational decision regarding efficient formulation and execution of suitable plans and projects or an objective assessment of their effectiveness, whether in the filed of industry, business or governmental activities, has necessarily to be based on objective data regarding resources and needs. There is, therefore, a need for various types of statistical (quantified) information to be collected and analyzed in an objective manner and presented suitably so as to serve as a sound basis for taking policy decisions in different fields of human activity. In modern times, the primary users of statistical data are the state, industry, business, scientific institutions, public organizations and international agencies.

Survey Data: From Sampling To Estimation

To obtain the data, the researcher needs to get observational access to the population of elements. The means for doing so is called a sampling frame.–the list of elements in the population, or–a way to make such a list, or–other mechanisms of selecting units (eg, RDD) The frame should be comprehensive, simple to use, organized in a systematic fashion (by geography, size, industry, etc.), able to unambiguously identify every element in any selected sample unit.

Designingand Coding Survey Instrumentsfor Statistical Analysis

2000

A forgollen part or generally ignored aspect of survey research is the preparation of the research instrument for suitable and efficient data entry and analysis. What ever is available appears to elude most researchers in the social sciences and humanities. The consequence is that these researchers, some of whom are authorities in their fields, frequently fall victim to poorly designed

A class project in survey sampling

College Teaching, 2002

Courses in quantitative methods typically require students to analyze previously collected data. There is great value in this exercise especially when they analyze data

Issn 0256 -422 X Effect of Measurement Errors on the Regression Method of Estimation in Survey Sampling

This article presents a framework for measurement errors in order to ana-lyze the properties of estimators in survey sampling and therefrom to ex-amine the effect of measurement errors. We consider a simple case in which information on merely one auxiliary characteristic is available and the re-gression method of estimation is used. First, we present two estimators of regression coefficient -one arising from direct regression and the other from reverse regression. Both the estimators are known to be inconsistent in the presence of measurement errors but when they are used to formulate es-timators of population mean of study characteristic, consistent estimators are obtained even when measurement errors are present. The large sample approximations for the biases and mean squared errors are derived and a comparison of the estimators that incorporate the auxiliary information is made with the traditional estimator that ignores the auxiliary information. The influence of measurement err...