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Survey design sits at the heart of political research—it's how we measure public opinion, test hypotheses, and gather the data that drives political analysis. You're being tested not just on recognizing different question types, but on understanding when and why researchers choose one format over another. The choice between a Likert scale and a ranking question isn't arbitrary; it reflects fundamental decisions about measurement validity, data analysis, and the kind of conclusions you can draw.
Think of question types as tools in a methodological toolkit. Each one captures different dimensions of opinion—intensity, preference, presence/absence, or open expression—and each comes with trade-offs between depth and standardization, nuance and comparability. When you encounter survey methodology on exams, don't just identify the question type—ask yourself what the researcher gains and loses by using it, and what kind of analysis it enables.
Closed-ended questions provide respondents with predefined answer options, making responses easy to code, compare, and analyze statistically. The trade-off is clear: you gain reliability and comparability at the cost of respondent freedom and potential insight into unexpected perspectives.
Compare: Multiple Choice vs. Dichotomous—both are closed-ended, but multiple choice allows gradation among options while dichotomous forces a binary split. Use dichotomous for screening; use multiple choice when you need to distinguish among several discrete categories.
Scaled questions move beyond simple categories to capture how much respondents agree, prefer, or feel about something. These formats recognize that opinions exist on a continuum and provide the ordinal or interval data needed for more sophisticated analysis.
Compare: Likert Scale vs. Semantic Differential—both measure intensity, but Likert focuses on agreement with statements while semantic differential captures associative meaning through adjective pairs. If an FRQ asks about measuring candidate image, semantic differential is your strongest example.
Some research questions require understanding not just what people think, but what they prioritize when forced to choose. These formats reveal the relative importance respondents assign to competing options—essential for understanding political decision-making.
Compare: Ranking vs. Rating Scale—rating scales let respondents evaluate each item independently (all could be "very important"), while ranking forces differentiation. Use ranking when you need to understand priorities; use rating when you want absolute evaluations. This distinction frequently appears in methodology questions.
Not all research questions can be anticipated in advance, and not all respondents fit neatly into predefined categories. Open-ended and contingency questions sacrifice standardization for richer, more tailored data collection.
Compare: Open-Ended vs. Closed-Ended—this is the fundamental trade-off in survey design. Open-ended provides depth and discovery; closed-ended provides comparability and efficiency. Strong research often uses both: closed-ended for hypothesis testing, open-ended for exploration and illustration.
| Concept | Best Examples |
|---|---|
| Measuring attitude intensity | Likert Scale, Rating Scale, Semantic Differential |
| Binary/categorical classification | Dichotomous, Multiple Choice |
| Revealing priorities and trade-offs | Ranking Questions |
| Efficient multi-item measurement | Matrix Questions |
| Qualitative depth and exploration | Open-Ended Questions |
| Adaptive survey flow | Contingency Questions |
| Standardized quantitative analysis | All Closed-Ended formats |
| Connotative/emotional meaning | Semantic Differential |
A researcher wants to understand which policy issues voters consider most important when they can only address three. Which question type best reveals these priorities, and why wouldn't a rating scale work as well?
Compare Likert scale and semantic differential questions: both measure attitudes, but what different dimensions of attitude does each capture?
You're designing a survey about candidate image. Which question type would best capture the feelings voters associate with a candidate (trustworthy-untrustworthy, strong-weak), and how does this differ from measuring policy agreement?
A pilot study aims to discover what concerns voters have about a new policy—concerns the researchers may not have anticipated. Which question type is most appropriate, and what trade-off does this choice involve?
Explain how contingency questions improve both respondent experience and data quality. Give an example of when a researcher would use one in a political survey.