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Saliency
Saliency refers to the degree to which a topic or event resonates with a prospective respondent or sample member. The more a topic or event resonates with a sample member, the more salient or important that topic or event tends to be in that person's life. Conversely, topics or events that resonate little or hold little importance for the sample member are said to have little saliency.
What are the implications of saliency for survey researchers? Saliency actually operates at two levels: the question level and the survey level.
On the question level, saliency refers to the importance of an event or action in a person's life. More important events or actions are better remembered than actions or events of low saliency. Consequently, saliency can affect the accuracy with which an event is remembered, which, in turn, can affect the accuracy of the response. More important or unusual events are generally remembered with greater accuracy than are common or frequent events. For example, most people can tell you, with little effort, their date of birth, the highest degree they have completed, what major illnesses they have suffered, or how many children they have. Similarly, given the significance of the event, many can tell you where they were when they heard the news of 9/11 or when John F. Kennedy was shot. Items of lesser importance, on the other hand, have lower saliency and are thus more difficult to remember. For example, recalling the number of times you have visited the grocery store in the past month or the number of movies you have seen in the past year can be difficult. On the other hand, while remembering how many movies you have seen in the past year is probably difficult, remembering the number of movies you have seen in the past week is probably not difficult. This illustrates an important point, the lower the saliency of an item, the shorter the reference period should be.
On the survey level, the saliency of the survey topic refers to the degree to which the subject matter of the survey resonates for the population being surveyed. If the questions being asked are of great interest to the average sample member, the survey is said to highly salient, whereas surveys where the subject being investigated is of little interest are said to have low saliency. Gaining cooperation or attaining a high response rate is made more difficult when the saliency is low, because sample members have little motivation to respond. On the other hand, when the central topic of a survey is one of great interest to those being surveyed, sample members are more likely to respond. For them, the burden of responding is compensated for by their interest in the topic. Thus, saliency is an important factor when thinking about response rates and the level of effort required to attain a certain response rate. For example, a questionnaire with high saliency and low respondent burden (e.g. takes minimal time to complete, is easy and straightforward to understand) will require much less effort to attain a high response rate than will a survey that has both low saliency and high respondent burden (i.e. takes a long time to complete, requires a great deal of record checking, or asks difficult or complex questions that require a great deal of thought). Surveys where the burden is high and the saliency is low often require respondent incentives to improve response rates.
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- Ethical Issues in Survey Research
- Anonymity
- Beneficence
- Cell Suppression
- Certificate of Confidentiality
- Common Rule
- Confidentiality
- Consent Form
- Debriefing
- Deception
- Disclosure
- Disclosure Limitation
- Ethical Principles
- Falsification
- Informed Consent
- Institutional Review Board (IRB)
- Minimal Risk
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- Privacy
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- Measurement - Interviewer
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- e
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- Nonresponse
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- Case
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- Operations - In-Person Surveys
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- Prefix
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- Telephone Consumer Protection Act 1991
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- Unpublished Number
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- Rolling Averages
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- Self-Selected Listener Opinion Poll (SLOP)
- Straw Polls
- Subgroup Analysis
- SUGing
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- Trend Analysis
- Trial Heat Question
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- Public Opinion
- Agenda Setting
- Consumer Sentiment Index
- Issue Definition (Framing)
- Knowledge Gap
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- Opinion Norms
- Opinion Question
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- Public Opinion Research
- Quality of Life Indicators
- Question Wording as Discourse Indicators
- Social Capital
- Spiral of Silence
- Third-Person Effect
- Topic Saliency
- Trust in Government
- Sampling, Coverage, and Weighting
- Adaptive Sampling
- Add-a-Digit Sampling
- Address-Based Sampling
- Area Frame
- Area Probability Sample
- Capture-Recapture Sampling
- Cell Phone Only Household
- Cell Phone Sampling
- Census
- Cluster Sample
- Clustering
- Complex Sample Surveys
- Convenience Sampling
- Coverage
- Coverage Error
- Cross-Sectional Survey Design
- Cutoff Sampling
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- Disproportionate Allocation to Strata
- Dual-Frame Sampling
- Duplication
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- Eligibility
- Email Survey
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- Equal Probability of Selection
- Error of Nonobservation
- Errors of Commission
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- Establishment Survey
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- Field Survey
- Finite Population
- Frame
- Geographic Screening
- Hagan and Collier Selection Method
- Half-Open Interval
- Informant
- Internet Pop-up Polls
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- Interpenetrated Design
- Inverse Sampling
- Kish Selection Method
- Last-Birthday Selection
- List Sampling
- List-Assisted Sampling
- Log-in Polls
- Longitudinal Studies
- Mail Survey
- Mall Intercept Survey
- Mitofsky-Waksberg Sampling
- Mixed-Mode
- Multi-Mode Surveys
- Multi-Stage Sample
- Multiple-Frame Sampling
- Multiplicity Sampling
- n
- N
- Network Sampling
- Neyman Allocation
- Noncoverage
- Nonprobability Sampling
- Nonsampling Error
- Optimal Allocation
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- Panel
- Panel Survey
- Population
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- Proportional Allocation to Strata
- Proxy Respondent
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- Quota Sampling
- Random
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- Random-Digit Dialing (RDD)
- Ranked-Set Sampling (RSS)
- Rare Populations
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- Replacement
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- Reverse Directory Sampling
- Rotating Panel Design
- Sample
- Sample Design
- Sample Size
- Sampling
- Sampling Fraction
- Sampling Frame
- Sampling Interval
- Sampling Pool
- Sampling without Replacement
- Screening
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- Self-Selection Bias
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- Superpopulation
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- Systematic Sampling
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- Telephone Surveys
- Troldahl-Carter-Bryant Respondent Selection Method
- Undercoverage
- Unit
- Unit Coverage
- Unit of Observation
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- Zero-Number Banks
- Survey Industry
- American Association for Public Opinion Research (AAPOR)
- American Community Survey (ACS)
- American Statistical Association Section on Survey Research Methods (ASA-SRMS)
- Behavioral Risk Factor Surveillance System (BRFSS)
- Bureau of Labor Statistics (BLS)
- Cochran, W. G.
- Council for Marketing and Opinion Research (CMOR)
- Council of American Survey Research Organizations (CASRO)
- Crossley, Archibald
- Current Population Survey (CPS)
- Gallup Poll
- Gallup, George
- General Social Survey (GSS)
- Hansen, Morris
- Institute for Social Research (ISR)
- International Field Directors and Technologies Conference (IFD&TC)
- International Journal of Public Opinion Research (IJPOR)
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- Journal of Official Statistics (JOS)
- Kish, Leslie
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- National Household Education Surveys (NHES) Program
- National Opinion Research Center (NORC)
- Pew Research Center
- Public Opinion Quarterly (POQ)
- Roper Center for Public Opinion Research
- Roper, Elmo
- Sheatsley, Paul
- Statistics Canada
- Survey Methodology
- Survey Sponsor
- Telemarketing
- U.S. Bureau of the Census
- World Association for Public Opinion Research (WAPOR)
- Survey Statistics
- Algorithm
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- Alternative Hypothesis
- Analysis of Variance (ANOVA)
- Attenuation
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- Balanced Repeated Replication (BRR)
- Bias
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- Data Swapping
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- Mean Square Error
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- Noncausal Covariation
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- Parameter
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- Percentile
- Point Estimate
- Population Parameter
- Post-Survey Adjustments
- Precision
- Probability
- Raking
- Random Assignment
- Random Error
- Raw Data
- Recoded Variable
- Regression Analysis
- Relative Frequency
- Replicate Methods for Variance Estimation
- Research Hypothesis
- Research Question
- Rho
- Sampling Bias
- Sampling Error
- Sampling Variance
- SAS
- Seam Effect
- Significance Level
- Solomon Four-Group Design
- Standard Error
- Standard Error of the Mean
- STATA
- Statistic
- Statistical Package for the Social Sciences (SPSS)
- Statistical Power
- SUDAAN
- Systematic Error
- t-Test
- Taylor Series Linearization
- Test-Retest Reliability
- Total Survey Error (TSE)
- Type I Error
- Type II Error
- Unbiased Statistic
- Validity
- Variable
- Variance
- Variance Estimation
- WesVar
- z-Score
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