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Evaluating the measurement error of interviewer observed paradata

Evaluating the measurement error of interviewer observed paradata
Evaluating the measurement error of interviewer observed paradata
As survey researchers have begun exploiting paradata—for example, for the correction of nonresponse bias—the quality of these data has come into question. Inaccurate information is likely to affect the resulting statistics and conclusions drawn from such data. This paper focuses on one type of paradata, observations made by interviewers during the data-collection process, and assesses the quality of these observations by examining their measurement error properties. The analysis uses the UK Census Nonresponse Link Study, which links interviewers’ observations collected on six major UK surveys with Census data. Comparing five interviewer observations with self-reports from the Census, the accuracy of the observations for both respondents and nonrespondents to the surveys is evaluated. A multilevel modeling approach is used to explore under which conditions the interviewers’ observations match the reports on the Census forms, accounting for the clustering of sample members within interviewers and areas. The analysis finds that the overall percent agreement between the observations and the Census is generally high, ranging from 87 to 98 percent. The type of housing structure and the final result code are significantly associated with measurement error. For four of the five observations, there is evidence that the interviewer significantly influences the level of measurement error, even after controlling for household, interviewer, and area characteristics. The results presented here will inform future analyses assessing the quality of interviewers’ observations.
0033-362X
173-193
Sinibaldi, Jennifer
9114a42c-726e-4d7b-812c-fb3a3f9b6a21
Durrant, Gabriele B.
14fcc787-2666-46f2-a097-e4b98a210610
Kreuter, Frauke
ef59c3bb-9474-44e2-b320-b83fe40affc8
Sinibaldi, Jennifer
9114a42c-726e-4d7b-812c-fb3a3f9b6a21
Durrant, Gabriele B.
14fcc787-2666-46f2-a097-e4b98a210610
Kreuter, Frauke
ef59c3bb-9474-44e2-b320-b83fe40affc8

Sinibaldi, Jennifer, Durrant, Gabriele B. and Kreuter, Frauke (2013) Evaluating the measurement error of interviewer observed paradata. [in special issue: Topics in Survey Measurement and Public Opinion] Public Opinion Quarterly, 77 (S1), 173-193.

Record type: Article

Abstract

As survey researchers have begun exploiting paradata—for example, for the correction of nonresponse bias—the quality of these data has come into question. Inaccurate information is likely to affect the resulting statistics and conclusions drawn from such data. This paper focuses on one type of paradata, observations made by interviewers during the data-collection process, and assesses the quality of these observations by examining their measurement error properties. The analysis uses the UK Census Nonresponse Link Study, which links interviewers’ observations collected on six major UK surveys with Census data. Comparing five interviewer observations with self-reports from the Census, the accuracy of the observations for both respondents and nonrespondents to the surveys is evaluated. A multilevel modeling approach is used to explore under which conditions the interviewers’ observations match the reports on the Census forms, accounting for the clustering of sample members within interviewers and areas. The analysis finds that the overall percent agreement between the observations and the Census is generally high, ranging from 87 to 98 percent. The type of housing structure and the final result code are significantly associated with measurement error. For four of the five observations, there is evidence that the interviewer significantly influences the level of measurement error, even after controlling for household, interviewer, and area characteristics. The results presented here will inform future analyses assessing the quality of interviewers’ observations.

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Published date: 2013
Organisations: Statistical Sciences Research Institute

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Local EPrints ID: 361613
URI: https://eprints.soton.ac.uk/id/eprint/361613
ISSN: 0033-362X
PURE UUID: fbcde294-9f26-4b2c-8e3c-8a27f52dca31

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Date deposited: 29 Jan 2014 13:24
Last modified: 03 Dec 2018 17:33

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