Live blogged at #PAPOR in San Francisco. Any errors or bad jokes are my own.
Enhancing the use of Qualitative Research to Understand Public Opinion, Paul J. Lavrakas, Independent Consultant; Margaret R. Roller, Roller Research
- thinks research has become to quantitative because qual is typically not as rigorous but this should and can change
- public opinion in not a number generated from polls, polls are imperfect and limited
- aapor has lost sight of this [you’re a brave person to say this! very glad to hear it at a conference]
- we need more balance, we aren’t a survey research organization, we are a public opinion organization, our conference programs are extremely biased quantitative
- there should be criteria to judge the trustworthyness of research – was it fit for purpose
- credible, transferable, dependability, confirmability
- all qual research should be credible, analyzable, transparent, useful
- credible – sample representation and data collection
- do qual researchers seriously consider non-response bias?
- credibility – scope deals with coverage design and nonresponse, data gathering – information obtained, researcher effects, participant effects
- analyzability – intercoder reliability, transcription quaity
- transparency – thick descriptions of details in final documents
Comparisons of Fully Balanced, Minimally Balanced, and Unbalanced Rating Scales, Mingnan Liu, Sarah Cho, and Noble Kuriakose, SurveyMonkey
- there are many ways to ask the same question
- is it a good time or a bad time? – fully balanced
- is it a good time or not? – minimally balanced
- do you or do you not think it is getting better?
- are things headed in the right direction?
- [my preference – avoid introducing any balancing in the question, only put it in the answer. For instance: What do you think about buying a house? Good time, Bad time]
- results – effect sizes are very small, no differences between the groups
- in many different questions tested, there was no difference in the formats
Conflicting Thoughts: The Effect of Information on Support for an Increase in the Federal Minimum Wage Level, Joshua Cooper & Alejandra Gimenez, Brigham Young University, First Place Student Paper Competition Winner
- Used paper surveys for the experiment, 13000 respondents, 25 forms
- Would you favor or oppose raising the minimum wage.
- Some were told how many people would increase their income, some were told how many jobs would be lost, some were told both
- Negative info opposed a wage increase, positive info in favor of wage increase, people who were told both opposed a wage increase
- independents were more likely to say don’t know
- negatively strongly outweighs the good across all types of respondents regardless of gnder, income, religion, partyID
- jobs matter, more than anything