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Quiz 3

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Survey Research

A data collection technique

in which information is collected

by having individuals respond to questions 

3 Types of survey research

Self-administered questionnaires

Interview surveys

Telephone surveys

Closed ended questions

The respondent is asked to select an answer

from among a fixed set of alternatives provided by the researcher

 

these are mutually exclusive categories

and exhaustive 

Open-ended questions

The respondent is asked to

provide his/her own answer to the question.

 

These are more exploratory

and used when all response categories are not known. 

Questions should be

Clear and unambiguous.

 

Avoid reference to things that arenot clearly defined or that respondents would have to interpret. 

Questions should  

Express only one idea.

Avoid double barreled questions. 

Question wording 

Should not be biased 

Six other things to think about in question design:
  1. Avoid negative items.
  2. Respondents must be competent to answer
  3. Respondents must be willing to answer
  4. Questions should be relevant.
  5. Short items are best.
  6. Be sure to pretest your instrument.
Compositve measures
Composed of several items that have a logical or empirical structure.
Answers to multiple questions are calculated together to form a value of construct by
  1. Summing the values of individual items
  2. Weighting and summing values of items.
Most standardized instruments are
Composite measures
3 formats of composite measures
  1. Likert scales
  2. Dichotomous questions
  3. Semantic differential format
Likert scales
A series of statements, each followed by 4 or 5 response alternatives
Semantic differential format
Respondents choose between two opposite positions on a ranked scale
2 ways to avoide response sets
  1. Make sure all items are not scaled in the same direction/reverse score items.
  2. Use an even number of response choices so that a middle or neutral option is not given.
4 methods of administrating social surveys 
  1. Computer assisted (i'net, computer/phone, laptop)
  2. Mail distribution
  3. Face-to-face interviewing
  4. Telephone interviewing
4 advantages of questionnaires
  1. Quick and inexpensive
  2. Allows one to collect data from geographically disperse locations
  3. Eliminates interviewer bias
  4. Good for sensitive issues
4 disadvantages of questionnaires
  1. Requires certain degree of literacy and facility in English
  2.  Questions must be sifficiently simple to comprehend
  3. No opportunity to probe
  4. Possible selection bias/low response rates (~20-90%)
Unstandardized interview guide approach
Least structured; interviewer has general topic area
Non-schedule-standardized
More structure; more narrow topic & specific questions asked of all respondents
Schedule-standardized interview guide approach
Interview schedule with specific questions; fixed order and transition phases are used.
5 advantages of interviews
  1. may collect more accurate and observational information
  2. Interviewer can explain questions and clarify answers
  3. Offers more control and more flexibility
  4. Higher response rates
  5. Good for complex issues
4 disadvantages of interviews
  1. Potential for interviewer bias/contamination of results by interviewer influence
  2. Safety concerns
  3. Increased costs
  4. Increased time for interviewer training and travel
Group depth interview
A facilitated interview with a whole group of people at the same time
5 adavantages of focus groups
  1. Able to assess people's subjective reactions
  2. Allows interviers to get at many levels of meaning
  3. Flexible
  4. Inexpensive
  5. Quick Results
2 disadvantages of focus groups
  1. Less generalizability
  2. Difficult to analyze - lots of information
4 items about secondary analysis of surveys
  1. Uses previously collected data
  2. Generally inexpensive and fast
  3. Questions aren't necessarily asked in the format that would best suit your research purpose
  4. May be misused (i.e., develop questions or hypotheses to fit the
4 reasons to draw a sample
  1. Some times entire population is too large to study
  2. A sample may be more time-efficient, more cost effective, & more feasible
  3. Samples can provide a close approximation of the population (limited by type of sampling techniques us
Element 
That unit about which information is collected and that provides the basis for analysis
Population
The theoretically-specified aggregation of study elements; all possible cases of what we are interested in studying and to whom we want to generalize
Study population
That aggregation of elements from which the sample is actually drawn
Sampling frame
A listing of all the elements in a population
Sample
One or more elements selected from a population
Representative sample
A sample that accurately reflects distribution of relevant variables in the population; allows generalization to population
2 types of sampling methods
  1. Probability sampling
  2. Non-probability sampling
Probability sampling

Each element has a chance, often equal, of being included in the sample.

 

Used for generalization to the population 

Non-probability sampling

The probability of each population element being included in the sample is not known; generally a less accurate representation of the population

 

Used when probability sampling is not an option or generalization is not needed. 

4 nonprobability sampling designs
  1. Convenience/availability
  2. Purposive/judgmental
  3. Quota sampling
  4. Snowball sampling
Convenience or availability sampling

Using elements readily available to the researcher

 

--cannot develop a complete sampling frame; exploratory

--not very accurate; cannot generalize 

Purposive/judgmental

Inverviewer's own judgment and prior knowledge of the population are used to choose persons for sample that best serve the purposes of the study

--provides some control of sample

--exploratory studies 

Quota sampling

Uses a matrix of the target populations characteristics to establish a quota sample specifying the number of elements to be selected from each category

 

--similar to stratified sampling

--used when sampling frame cannot be estab

Snowball sampling

Collect data on the few members of target population available, then request them for information leading to more people, who lead to more people, and so on

 

--good for hard to access populations

--often used in qualititative fi

Random selection
Each element has an equal chance of being selected
Parameter
Aggregate data from a population; the summary description of a given variable in a population
Statistic
Aggregate data from a sample; the summary description of a given variable in a sample; used to estimate population parameters
Standard error
Estimate of the extent to which the values of the sample differ from those of the population.
Probability theory

Ultimate purpose of sampling is to selecta set of elements from a population so that sample statistics accurately portray total population parameters.

--requires random selection 

Sampling distribution
Theoretically taking repeated random samples of a single population and plotting the summary statistics on a graph
Probability theory states that if we collected all possible samples of a population, the statistical means would cluster in a formation called
a normal curve, such that the distribution of sample statistics cluster around the population parameter in a known way

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