Rethinking Leverage-Salience Theory and Causes of Survey Nonresponse:

1. Rethinking Leverage-Salience Theory and Causes of Survey Nonresponse: Integrating Emotion, Mood, and Affect into Theory of Nonresponse Matt Jans US Census Bureau, Statistical Research Division Rachel Levenstein Michigan Program in Survey Methodology University of Michigan

2. Scope • What makes up leverage? • Affect v. Reasoned judgment • Application of random effects w/in LST • Affect • Design features

3. Leverage-Salience Theory (LST)(Groves, Singer, & Corning, 2000) • Addresses correlates and causes of unit refusal nonresponse • Probability of response for the individual is a combination of • Leverage of a survey attribute • Salience of the same survey attribute

4. Visual Model of LSTGroves, Singer, & Corning (2000), p. 300

5. Definition and Examples of Leverage • “The sample person’s assessment of a particular attribute of a survey” (Groves, et al., 2000) • Incentive: Economic need or social exchange • Survey Topic: Interest in or commitment to issue • Survey Mode: Enjoyment of or aversion to interacting w/ a live person (e.g., temperament or social isolation)

6. Definition and Examples of Salience • Awareness of the sampled person to the survey feature • Explanation of topic, mode, incentive in cover letter or interviewer recruitment script • Obvious presence of survey feature (e.g., $5 bill clipped to survey; Interviewer on doorstep)

7. Decomposing Leverage Leverage = Valence + Distance Valence is positive or negative • Positively valenced features dispose the sampled person toward participation • Negatively valenced features dispose the sample person toward refusal

8. Focus of the Talk

9. Decomposing Valence • No explicit distinction between causes of valence • All cognitive, emotional, judgmental psychological actions are pooled

10. Definitions of Affect • Affect • Mood • Non-directed, lower-intensity, longer-lasting • Emotion • Directed at an object/cause, higher-intensity, acute

11. Affect and Decision Making • “Feelings as Information” perspective • Affect impacts/operates in information processing, judgment and memory (Schwarz & Clore, 2007) • We often make judgments and decisions on affective or emotional information (Schwarz & Clore, 2007; Schwarz, 2000) • We perceive the world emotionally first (Zajonc, 1980)

12. Major Findings on Affect and Decision Making • Depressed v. positive mood • Strong arguments more effective for people in sad or negative moods, than positive moods (Schwarz, 2000) • Mood will influence responses unless there is an attributable cause • Weather & well-being (Schwarz & Clore, 1983)

13. Incorporating Affect into LST

14. Incorporating Affect into LST • Affect related to design features (integral affect) • Like or dislike interacting with another person or not (SAQ v. Iwr Admin Modes)? • Feel that the incentive is a “fair trade” or manipulative? • Does R have strong feelings (positive or negative) about the survey topic or sponsor?

15. Incorporating Affect into LST • Random effect of design features • Design feature is one realization of similar features (e.g. levels of incentive, personalization of letter) • Repeated measures from different levels-features across same R’s ln[pij/(1-pij)]=B0 + B1ijAffDesij + B2iSij + u1iAffDesij + eij i=Respondent , j=Design Feature

16. Incorporating Affect into LST • Affect unrelated to design features (incidental affect) • The mind state we happen upon when requesting survey participation • Daily/weekly variation in mood • Individual variation in mood • Societal variation in mood (e.g., anxious mood due to economic situation; saturation with polling)

17. Incorporating Affect into LST • Random effect of respondent • Respondent’s propensity may change over time irrespective of design feature • Repeated measures from same respondent receiving same design features ln[pij/(1-pij)]=B0 + B1ijAffRespij + B2iSi + u1iAffRespij + eij i=Respondent , j=Recruitment Attempt

18. Collection of Measures • Voice and speech indicators of mood • Respondent speech (spoken words) • Coded for affective content • “I don’t feel comfortable answering questions about my sex life” • Interviewer or observer rating of affect • Respondent rating of own affector design featares

19. Collection of Measures • Complexity of measures will depend on definition of affect • Integral: Affect related to survey design features • Measures collected from initial contact with R • Incidental: Affect unrelated to survey • Voice at contact • Measures need to be taken outside of the interaction with the survey • Non-contact v. Refusal • Panel data helpful

20. Links to Other Error Sources • Measurement Error • Response by individuals with only positive affective states would bias measures of affect or wellbeing • Identifying current mood & assigning it to a cause (e.g. weather) can change satisfaction reports • Item Nonresponse • Similar mechanisms & opportunities for tailoring apply

21. International Component • Cultural differences in social cognition & emotion (Markus & Kitayama, 1991)

22. References Bachorowski, J. A. (1999). Vocal expression and perception of emotion. Current Directions in Psychological Science, 8(2), 53-57. Groves, R. M., Couper, M. P., Presser, S., Singer, E., Tourangeau, R., Acosta, G. P., & Nelson, L. (2006). Experiments in producing nonresponse bias. Public Opinion Quarterly, 70(5), 720-736. Groves, R. M., Presser, S., & Dipko, S. (2004). The role of topic interest in survey participation decisions. Public Opinion Quarterly, 68(1), 2-31. Groves, R. M., Singer, E., & Corning, A. (2000). Leverage-saliency theory of survey participation: Description and an illustration. Public Opinion Quarterly, 64(3), 299-308. Markus HR, Kitayama S. Culture and the self: Implications for cognition, emotion, and motivation. Psychological Review. 1991;98(2):224-253. Available at: http://doi.apa.org/getdoi.cfm?doi=10.1037/0033-295X.98.2.224. Roose, H., Lievens, J., & Waege, H. (2007). The joint effect of topic interest and follow-up procedures on the response in a mail questionnaire: An empirical test of the leverage-saliency theory in audience research. Sociological Methods & Research, 35(3), 410. Schwarz, N. (2000). Emotion, cognition, and decision making. Cognition and Emotion, 14(4), 433-440. Schwarz N, Clore GL. Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. Journal of Personality and Social Psychology. 1983;45(3):513-523. Available at: http://content.apa.org/journals/psp/45/3/513. Schwarz, N., & Clore, G. L. (2007). Feelings and emotional experiences.In A. W. Kruglanski, & E. T. Higgins, Social Psychology: Handbook of Basic Principles, (pp. 385-407). Guilford Press. Zajonc, R. B. (1980). Feeling and thinking: Preferences need no inferences. American Psychologist, 35(2), 151-175.

23. Thank You • matthew.e.jans@census.gov • mlev@isr.umich.edu

24. LST Findings • “Peripheral” aspects of surveys (e.g., incentive, follow-up protocol) have larger impact in absence of personal relevance of topic (Groves, et al., 2000; Roose, Lievens, & Waege, 2007) • Personal relevance does not always lead to increased response (Groves, Couper, Presser, et al, 2006; Groves, Presser, & Dipko, 2004)

25. Understanding Leverage • Hard to measure • Internal, subjective • Group membership • Decompose leverage into components to facilitate measurement • Affective v. reasoned perceptions and judgments of survey request

26. Integrating Affect into Survey Practice • Tailoring to affect states • “I’m sure you’ve had a busy day” if calling in evening • Listen for vocal cues indicating unease and tailor • Different information/arguments required for different moods • Moods may be changeable