Sampling and Construction of Variables

Jean-Michel Josselin and Benoît Le Maux
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Jean-Michel Josselin: University of Rennes 1
Benoît Le Maux: University of Rennes 1

Chapter 2 in Statistical Tools for Program Evaluation, 2017, pp 15-43 from Springer

Abstract: Abstract The construction of a reliable and relevant database is a key aspect of any statistical study. Not only will misleading information create bias and mistakes (sampling, coverage or measurement errors, etc.), but it may also seriously affect public decisions if the study is used for guiding policy-makers. The sample should be sufficiently representative of the population of interest (Sect. 2.1). The time needed to collect and process the data is an important issue in this respect (Sect. 2.2). As the purpose of a survey is to obtain sincere responses from the respondents, the design of the questionnaire also has its importance; in particular the sequencing, phrasing and format of questions (Sect. 2.3). The process of data collection should not be neglected either. The analyst must decide which sampling method is more relevant (e.g., non-probability vs. probability sampling) and assess the efficacy of data collection during the survey process (Sect. 2.4). Last, the coding of variables and the way measurement and nonresponse errors are investigated are an essential step of data construction (Sect. 2.5).

Keywords: Census; Survey; Questionnaire; Sampling; Coding; Nonresponse errors; Outliers; Raking (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/978-3-319-52827-4_2

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