In Europe, list frame sampling methods are often adopted in computer-assisted telephone interviewing surveys. When sampling frames (i.e., white pages) are incomplete, the quality of the resulting survey data may be seriously jeopardised. In 2012, only 50% of Italians are included in the sampling frame; the remaining are excluded, as they do not own a landline telephone (32%) or their landline telephone number is unlisted (18%). This paper explores differences in the socioeconomic and demographic characteristics of different sub-samples of respondents, investigates the impact of telephone under-coverage on a set of items belonging to different survey domains, and assesses the effectiveness of current weighting procedures. We find that under-coverage leads to bias and that a “one size fits all” weighting strategy can hardly be considered as an accurate method to correct for noncoverage bias
Sala, E., Lillini, R. (2017). Undercoverage bias in telephone surveys in Europe: The Italian case. INTERNATIONAL JOURNAL OF PUBLIC OPINION RESEARCH, 29(1), 133-156 [10.1093/ijpor/edv033].
Undercoverage bias in telephone surveys in Europe: The Italian case
SALA, EMANUELA MARIA
Primo
;LILLINI, ROBERTOUltimo
2017
Abstract
In Europe, list frame sampling methods are often adopted in computer-assisted telephone interviewing surveys. When sampling frames (i.e., white pages) are incomplete, the quality of the resulting survey data may be seriously jeopardised. In 2012, only 50% of Italians are included in the sampling frame; the remaining are excluded, as they do not own a landline telephone (32%) or their landline telephone number is unlisted (18%). This paper explores differences in the socioeconomic and demographic characteristics of different sub-samples of respondents, investigates the impact of telephone under-coverage on a set of items belonging to different survey domains, and assesses the effectiveness of current weighting procedures. We find that under-coverage leads to bias and that a “one size fits all” weighting strategy can hardly be considered as an accurate method to correct for noncoverage biasFile | Dimensione | Formato | |
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