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Solving the Problem of Attrition in Longitudinal Surveys: Effects of Interviewer Continuity Peter Lynn, Olena Kaminska University of Essex and Harvey Goldstein.

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Presentation on theme: "Solving the Problem of Attrition in Longitudinal Surveys: Effects of Interviewer Continuity Peter Lynn, Olena Kaminska University of Essex and Harvey Goldstein."— Presentation transcript:

1 Solving the Problem of Attrition in Longitudinal Surveys: Effects of Interviewer Continuity Peter Lynn, Olena Kaminska University of Essex and Harvey Goldstein University of Bristol

2 Same vs. Different Interviewer: Does it Make a Difference? Theoretical evidence: -Trust (not a stranger, not a sales person, not a criminal) -Consistent behaviour -Interviewer may tailor the introduction / door-step conversation -Possibly harder to refuse to an acquaintance Empirical evidence shortcomings: -Interviewer change doesn’t happen randomly – e.g. bad interviewers quit -Comparing same vs. different interviewers isn’t straightforward – e.g. same interviewers are promoted within a year.

3 Data Sample: participants of the March Omnibus 2008, who agreed to be revisited and provided a contactable name Re-contacted in 2009 as part of Omnibus Follow-up respondents reissued (1097 eligible for analysis excluding movers and ineligible) Questionnaire topic: Perceptions of Safety on Public Transport Response rate: 77% (refusals – 14%; noncontact – 3.5%)

4 Experimental 2-way Balanced Design: interviewer change crossed with grade change Same Interviewer Lowest grade 2009 Middle grade 2009 Highest grade 2009 Lowest grade Middle grade Highest grade Different InterviewersSame Interv. Lowest grade 2009 Middle grade 2009 Highest grade 2009 Lowest grade Middle grade Highest grade

5 Multilevel Analysis: Multiple Membership Model Interviewers Respondents % of variance within 2009 interviewers 15% of variance within 2008 interviewers

6 Results: Interviewer Continuity Influence on Response Rate Same InterviewerDifferent Interviewer same (low) same (mid) same (high) high er (all) lower (mid- low) lower (high- low) lower (high- mid) same (low) same (mid) same (high higher (low- mid) higher (low- high) higher (mid- high) Same int-er same (low) same (mid) + same (high) + + higher (all) Different interviewer lower (mid-low) * -.97* - lower ( high-low) * -.94* - + lower (high-mid) same (low) * -.93* same (mid) * * same (high) *-1.02* higher (low-mid) higher (low-high) higher (mid-high) * Base- line

7 Results: Interviewer Continuity Influence on Response Rate Same InterviewerDifferent Interviewer same (low) same (mid) same (high) high er (all) lower (mid- low) lower (high- low) lower (high- mid) same (low) same (mid) same (high higher (low- mid) higher (low- high) higher (mid- high) Same int-er same (low) same (mid) + same (high) + + higher (all) Different interviewer lower (mid-low) * -.97* - lower ( high-low) * -.94* - + lower (high-mid) same (low) * -.93* same (mid) * * same (high) *-1.02* higher (low-mid) higher (low-high) higher (mid-high) * Base- line

8 Results: Interviewer Continuity Influence on Response Rate Same InterviewerDifferent Interviewer same (low) same (mid) same (high) high er (all) lower (mid- low) lower (high- low) lower (high- mid) same (low) same (mid) same (high higher (low- mid) higher (low- high) higher (mid- high) Same int-er same (low) same (mid) + same (high) + + higher (all) Different interviewer lower (mid-low) * -.97* - lower ( high-low) * -.94* - + lower (high-mid) same (low) * -.93* same (mid) * * same (high) *-1.02* higher (low-mid) higher (low-high) higher (mid-high) * Base- line

9 Further Development of the Model Respondent Characteristics -Age -Gender -Education -Marital status -Number of adults in the HH -Kids -Tenure -Employment -General health -Disability Interviewer Observations -Area condition -House condition in comparison to neighbouring houses -House type Main effects, random effects and interactions of interviewer continuity with the following variables:

10 Final Model Response Rate = intercept + interviewer continuity + age + employment + tenure + house condition + area condition + education + education*house ownership + interviewer continuity*employment + random effect of age 95% of variance within 2009 interviewers 5% of variance within 2008 interviewers

11 Predicted Likelihood to Respond as a Function of Interviewer Continuity*Employment Status Employed Unemployed

12 Predicted Likelihood to Respond as a Function of Interviewer Continuity and Age (random effect)

13 Conclusions Same interviewer performs the same or better than a different interviewer in obtaining an interview in wave 2 of the study There is no evidence that sending a different interviewer with higher grade improves the chances of obtaining an interview in comparison to keeping the same interviewer There is no evidence that changing interviewer increases attrition rate in wave 2 if a respondent was initially approached by an interviewer of low grade

14 Conclusions Conditional on an interview by the highest grade interviewer in the first wave, interviewers of the highest grade are 2.8 times more likely to obtain an interview in the 2 nd wave if they interviewed the same respondent in previous wave Same interviewer with the highest grade has the lowest attrition. It is a positive point considering that initially a number of hard refusals agreed to participate when approached by an interviewer of highest grade Response in the second wave is more influenced by the interviewer in the second wave than by the interviewer in the first wave (ratio ranging from 85/15 to 95/05).

15 Thoughts Future studies of interviewer continuity should look at interviewer change controlled by interviewer experience Interaction of interviewer characteristics with respondent characteristics should be explored for potential tailoring Same or different interviewers have effect on other aspects of survey, for example on consistency of responses or measurement error. This needs to be taken into account when making a decision. It is of interest to look at specific conditions where interviewer change may be beneficial

16 Thank you Corresponding author: Olena Kaminska,


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