1. Survey Methodology Nonresponse EPID 626 Lecture 6

2. Lecture Overview Finish discussion of computer-assisted interview Discuss nonresponse

3. Computer assisted survey More of a tool than a design really –Can be used as a stand-alone self- administered survey –Can be used in conjunction with telephone or personal interviews –Can use in conjunction with video to simulate a personal interview If desired, you can match some characteristics, such as age, race, and gender of the interviewer with the subject (more on this later)

4. Computer assisted survey (2) Available information? –Depends on other elements of the study design Survey population skills and motivation? –People who are not familiar with computers may feel uncomfortable –Can adjust the language –Can read questions aloud

5. Computer assisted survey (3) Desired data? –Can follow complex question patterns or questions tailored to previous answers –Can identify inconsistencies or missing data before the interview is over –Can be useful in combination with telephone survey

6. Computer assisted survey (3) Response rates? –Depends on other elements of the study design Resources? –No data entry required –If it is self-administered, no interviewer required

7. What is nonresponse? The failure to collect data from subjects selected to be in the sample Potentially one of the most important sources of systematic error in a study Unlike like random error, such as sampling error, nonresponse tends to bias estimates

8. 3 categories of nonresponders Those whom the data collection procedures do not reach Those who refuse to provide data Those who are unable to provide data

9. Response rate Number of respondents X100% Number sampled Rule of thumb for minimum response rate is 75% (Fowler, 1993) –adequate 50% –good 60% –very good 75% (Babbie, 1990)

10. Bias due to nonresponse The bias is a function of: the response rate the extent to which nonresponders differ from the sample population

11. Generalizations Response rates are higher in rural areas than in urban areas Response rates are lower when there is a designated respondent than if you take any responsible adult Response rates are higher for topics that interest people

12. Why are response rates lower in urban areas? Higher proportion of single individuals More highrise dwellings (less accessible) Interviewers may be uncomfortable in urban areas at night

13. Do response rates differ by data collection method?

14. Mail surveys Those with an interest are more likely to respond Better educated people are more likely to respond This method generally has the lowest response rates, but with effort, response rates can be attained that are comparable to other methods

15. Phone and personal interview Availability bias-more likely to get housewives, unemployed, retirees, those with children, large households

16. Maximizing response rates in mail surveys Make the survey attractive and professional looking –use green paper Professional endorsement Prenotification Offer a monetary incentive

17. Maximizing response rates in mail surveys Make the survey quick and simple Include stamped, addressed return envelopes Mail reminders to nonresponders –usually every two weeks Follow-up nonresponders by telephone

18. Maximizing response in phone and personal interviews Vary call times, repeat unsuccessful calls Have flexible interview times Send informational letters ahead of time Communicate the survey purpose and importance to participant Use effective interviewers

19. Correcting for nonresponse Use proxy respondents Use statistical adjustments such as weighting subgroups to match their rate in the sample population Survey nonrespondents

20. Correcting for nonresponse(2) Wave analysis-compare those who responded in your first wave to those who responded only after follow-up –Assume that late responders are similar to nonresponders Calculate the pattern of response in nonresponders needed to reverse the study conclusions

21. Survey nonrespondents Can survey with a pared-down instrument that contains only those variables that you expect to differ from sample population values or outcome variables of greatest interest

22. In this case, stratify the calculation of sample estimate: