One of the main purposes of modern statistics is to ensure high quality data release necessary to satisfy expectations of their users and enable them to take effective political decisions. Statisticians struggle with this important problem mainly by seeking how to minimise response burden – one of the main barriers hampering the completion of this task. The burden can result both from the methodological design and survey management and from the respondent or technical support.
In this module we present the essence of response burden, analyse fundamental concepts related to this problem (with some original recommendations) and list the main types of difficulties which arise depending on the approach adopted. The importance and causes of the burden are discussed in detail. We also characterise the most important methods of measuring burden (both actual and perceived, also in the complex form) and their effects. In this context, we assess the efficiency of the burden reduction methods by referring to the assumptions of the Standard Cost Model. Practical examples of observed difficulties are presented. Basic and selected special methods to minimise these difficulties and international recommendations are also discussed.
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