Back in September
a PSC Research Project
Investigator: Frederick G. Conrad
While the sample survey is one of the cornerstones of social science research methods, the tool is experiencing large declines in participation of sampled persons. This project studies participation in cross-section Random-Digit Dialed (RDD) telephone surveys. The declines have led to such significant research cost increases that serious consideration of terminating basic surveys is occurring. Thus, while nonparticipation can induce statistical errors affecting inference to the target population, one does not have to value nonresponse rates as solely an indicator of potential bias.
One large source of variation in RDD cooperation rates is the interviewer. In centralized telephone interviewing facilities interviewers are often assigned similar mixes of cases, yet obtain very different response rates. All the stimuli yielding a decision to participate in an RDD survey must be delivered through audio channel – through words, pitch, inflection, and pacing of the interviewers’ speech. These attributes are not the traditional objects of study of survey methodologists. Hence, the project combines insights from speech science, phonetics, psycholinguistics, and survey methodology. A central conceptual framework utilizes the companion notions of tailoring, convergence, and similarity in cooperative dyadic communication.
An interdisciplinary team at Michigan and Michigan State (with consultation from Columbia) will transform about 5,000 digital audio recordings of RDD telephone interviewer introductions (from two data collection organizations, 6 different surveys, and 165 different interviewers) into a quantitative data set suitable for dynamic and static statistical models of response propensities. Acoustic measures motivated by concepts from speech science will be extracted using Praat acoustic software; raters will make judgments of perceived attributes of speakers using both concepts central to leverage-salience theory and the social psychology; and word and disfluency rates will be extracted from transcriptions of the audio files.
The resulting data set is a relational one with records at the levels of the interviewer, respondent (case), contact, and conversational turn. Hierarchical and survival models will be built using the combined conceptual frameworks predicting the final participation decision of a sample case.
|Funding:||National Science Foundation (SES 0819734)|
Funding Period: 09/15/2008 to 08/31/2011