Approximated Synthetic Indicator for Total Errors in Abu Dhabi Sample Surveys

Mohammed Al Rifai


A central role of national statistical organizations is to support the comprehensive development of their countries, through the provision of reliable high quality official statistics. There are different definitions for “quality” because of differences in the objectives sought. The concept of quality is no longer limited to the product-accuracy level, but has become more far-reaching, in a way that it comprises other quality dimensions, such as institutional arrangement supporting quality, data accuracy, relevance, clarity and interpretability, sound methodology, timeliness and punctuality, data accessibility, and consistency and coherence. End users mostly concentrate on the data accuracy dimension. The Statistics Centre Abu Dhabi (SCAD) has used to evaluate the data quality, including accuracy dimension in each implementation phase of the sample survey, based on a pre-determined checklist of quality standards that should be achieved. The outcome of this assessment method is a nominal measure to classify the quality in each survey phase as a Low, Medium, or High level of quality. Moderate data users and policy makers concentrate more on a quantitate measure of the total survey error, rather than a subjective or nominal measure.This paper aims to propose statistical methodology to compile approximated synthetic indicator to measure the total survey errors based on the different sources of statistical errors that could be committed in all survey phases.

Keywords: Quality, statistical error, accuracy.

DOI: 10.7176/JESD/10-22-07

Publication date: November 30th 2019

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