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Verbal Paradata and Survey Error: Respondent Speech, Voice, and Question-Answering Behavior can Predict Income Item Nonresponse.

dc.contributor.authorJans, Matthew E.en_US
dc.date.accessioned2010-06-03T15:45:28Z
dc.date.availableNO_RESTRICTIONen_US
dc.date.available2010-06-03T15:45:28Z
dc.date.issued2010en_US
dc.date.submitteden_US
dc.identifier.urihttps://hdl.handle.net/2027.42/75932
dc.description.abstractIncome nonresponse is a significant problem in survey data, with rates as high as 50%, yet we know little about why it occurs. It is plausible that the way respondents answer survey questions (e.g., their voice speech, and question-answering behavior) can predict whether they will provide income data, and reflect the psychological states that produce this decision. Five questions each from 185 recorded interviews conducted by the Surveys of Consumers were selected. One was the annual household income question. Exchanges between interviewers and respondents were transcribed and coded for respondent speech and question-answering behavior. Voice pitch was extracted mechanically using the Praat software. Speech, voice, and question-answering behaviors are used as verbal paradata; characteristics of the survey process that are not captured by default. Verbal paradata are hypothesized to reflect respondents' affective and cognitive states, which then predict income nonresponse. It was hypothesized that indicators of respondent affect (e.g., pitch) and cognitive difficulty (e.g., disfluency) would be affected by sensitive and complex questions differently, and would predict whether respondents provide income in a dollar amount, a bracketed range of values, or not at all. Results show that verbal paradata can distinguish between income nonrespondents and respondents, even when only using verbal paradata that occur before the income question. Income nonrespondents have lower affective involvement and express more negativity before the income question. Bracketed respondents express more signs of cognitive difficulty. Income nonresponse is predicted by behavior before the income question, while bracketed response is predicted by indicators on the income question itself. Further, question characteristics affect respondent paradata, but largely in unpredicted ways. There is evidence for psychological resource and conversationality mechanisms through which respondents reduce verbal paradata when questions are demanding, rather than increasing it as signs of trouble. The results have implications for theory of income nonresponse, specifically the role of question characteristics and respondent paradata in understanding what subjective psychological states respondents are experiencing when they answer survey questions, and how those states predict whether income is reported. There are also potential extensions to interviewer training and design of interventions that could produce more complete income data.en_US
dc.format.extent2065463 bytes
dc.format.extent1373 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_USen_US
dc.subjectSurvey Methodologyen_US
dc.subjectIncome Data Qualityen_US
dc.subjectItem Nonresponseen_US
dc.subjectSurvey Erroren_US
dc.subjectPsychology of Survey Responseen_US
dc.subjectEmotion, Affect, and Cognitionen_US
dc.titleVerbal Paradata and Survey Error: Respondent Speech, Voice, and Question-Answering Behavior can Predict Income Item Nonresponse.en_US
dc.typeThesisen_US
dc.description.thesisdegreenamePhDen_US
dc.description.thesisdegreedisciplineSurvey Methodologyen_US
dc.description.thesisdegreegrantorUniversity of Michigan, Horace H. Rackham School of Graduate Studiesen_US
dc.contributor.committeememberConrad, Frederick G.en_US
dc.contributor.committeememberLepkowski, James M.en_US
dc.contributor.committeememberBenki, Jose R.en_US
dc.contributor.committeememberFowler Jr, Floyd Jacksonen_US
dc.contributor.committeememberKreuter, Fraukeen_US
dc.contributor.committeememberSchwarz, Norbert W.en_US
dc.subject.hlbsecondlevelPsychologyen_US
dc.subject.hlbsecondlevelSocial Sciences (General)en_US
dc.subject.hlbsecondlevelSociologyen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/75932/1/mattjans_1.pdf
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


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