Chapter 12 Flashcards
Earliest use of surveys
Survey research may have its roots in English and American “social surveys” conducted around the turn of the 20th century by researchers and reformers who wanted to document the extent of social problems such as poverty (Converse, 1987)[1].
Cognitive Model of responding to a survey:
Respondents must interpret the question, retrieve relevant information from memory, form a tentative judgment, convert the tentative judgment into one of the response options provided (e.g., a rating on a 1-to-7 scale), and finally edit their response as necessary.
Context Effects:
Unintended influences on respondents’ answers because they are not related to the content of the item but to the context in which the item appears.
Item-Order effect
For example, there is an item-order effect when the order in which the items are presented affects people’s responses. One item can change how participants interpret a later item or change the information that they retrieve to respond to later items.
How to fight order effects:
To mitigate against order effects, rotate questions and response items when there is no natural order. Counterbalancing or randomizing the order of presentation of the questions in online surveys are good practices for survey questions and can reduce response order effects that show that among undecided voters, the first candidate listed in a ballot receives a 2.5% boost simply by virtue of being listed first[6]!
Open-Ended questionnaire items:
Open-ended items simply ask a question and allow participants to answer in whatever way they choose.
Open-ended items are relatively easy to write because there are no response options to worry about. However, they take more time and effort on the part of participants, and they are more difficult for the researcher to analyze because the answers must be transcribed, coded, and submitted to some form of qualitative analysis, such as content analysis. Another disadvantage is that respondents are more likely to skip open-ended items because they take longer to answer. It is best to use open-ended questions when the answer is unsure or for quantities which can easily be converted to categories later in the analysis.
Closed-ended questionnaire items
Closed-ended items ask a question and provide a set of response options for participants to choose from.
What is a rating scale?
A rating scale is an ordered set of responses that participants must choose from.
Likert Scale
In reading about psychological research, you are likely to encounter the term Likert scale. Although this term is sometimes used to refer to almost any rating scale (e.g., a 0-to-10 life satisfaction scale), it has a much more precise meaning.
In the 1930s, researcher Rensis Likert (pronounced LICK-ert) created a new approach for measuring people’s attitudes (Likert, 1932)[8]
BRUSO
An acronym that stands for “brief,” “relevant,” “unambiguous,” “specific,” and “objective,” which is used to create effective questionnaire items that are brief and to the point.
Double-barrelled questions
A common problem here is closed-ended items that are “double barrelled.” They ask about two conceptually separate issues but allow only one response. For example, “Please rate the extent to which you have been feeling anxious and depressed.” This item should probably be split into two separate items—one about anxiety and one about depression.
How many response options should you allow?
For rating scales, five or seven response options generally allow about as much precision as respondents are capable of. However, numerical scales with more options can sometimes be appropriate
Every survey should have a ____ or ___ introduction.
Written, Spoken.
What are the two purposes of a survey introduction?
- Encourage participants to participate in a survey.
- Establish informed consent.
What should come after a survey introduction?
-Instructions
-Most important questions
-Less important questions
-Least important questions
What are the 2 categories of sampling?
Probability Sampling - This occurs when the researcher can specify the probability that each member of the population will be selected for the sample.
Non-Probability sampling - This occurs when the researcher cannot specify the probability that each member of the population will be selected for the sample.
What is convenience sampling?
Convenience sampling—studying individuals who happen to be nearby and willing to participate—is a very common form of non-probability sampling used in psychological research.
Other types of Non-probability sampling:
Other forms of non-probability sampling include snowball sampling (in which existing research participants help recruit additional participants for the study), quota sampling (in which subgroups in the sample are recruited to be proportional to those subgroups in the population), and self-selection sampling (in which individuals choose to take part in the research on their own accord, without being approached by the researcher directly).
SAMPLING FRAME
Once the population has been specified, probability sampling requires a sampling frame. This sampling frame is essentially a list of all the members of the population from which to select the respondents. Sampling frames can come from a variety of sources, including telephone directories, lists of registered voters, and hospital or insurance records. In some cases, a map can serve as a sampling frame, allowing for the selection of cities, streets, or households.
Simple Random Sampling
A probability sampling method in which each individual in the population has an equal probability of being selected for the sample.
STRATIFIED Random Sampling
A common alternative to simple random sampling in which the population is divided into different subgroups or “strata” (usually based on demographic characteristics) and then a random sample is taken from each “stratum.”
Proportionate Random Sampling
Is used to select a sample in which the proportion of respondents in each of various subgroups matches the proportion in the population.
Disproportionate Stratified Random Sampling
Is used to sample extra respondents from particularly small subgroups—allowing valid conclusions to be drawn about those subgroups.
Cluster Sampling
A type of probability sampling in which larger clusters of individuals are randomly sampled and then individuals within each cluster are randomly sampled. This is the only probability sampling method that does not require a sampling frame.