Statistical Survey Information
In statistics, survey methodology is the field that studies the sampling of individuals from a population with a view towards making statistical inferences about the population using the sample. Polls about public opinion, such as political beliefs, are reported in the news media in democracies. Other types of survey are used for scientific purposes. Surveys provide important information for all kinds of research fields, e.g., marketing research, psychology, health professionals and sociology.[1] A survey may focus on different topics such as preferences (e.g., for a presidential candidate), behavior (smoking and drinking behavior), or factual information (e.g., income), depending on its purpose. Since survey research is always based on a sample of the population, the success of the research is dependent on the representativeness of the population of concern (see also sampling (statistics) and survey sampling).
Survey methodology seeks to identify principles about the design, collection, processing, and analysis of surveys in connection to the cost and quality of survey estimates. It focuses on improving quality within cost constraints, or alternatively, reducing costs for a fixed level of quality. Survey methodology is both a scientific field and a profession. Part of the task of a survey methodologist is making a large set of decisions about thousands of individual features of a survey in order to improve it.[2]
The most important methodological challenges of a survey methodologist include making decisions on how to:[2]
- Identify and select potential sample members.
- Contact sampled individuals and collect data from those who are hard to reach (or reluctant to respond).
- Evaluate and test questions.
- Select the mode for posing questions and collecting responses.
- Train and supervise interviewers (if they are involved).
- Check data files for accuracy and internal consistency.
- Adjust survey estimates to correct for identified errors.
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Selecting samples
Main article: Survey samplingSurvey samples can be broadly divided into two types: probability samples and non-probability samples. Stratified sampling is a method of probability sampling such that sub-populations within an overall population are identified and included in the sample selected in a balanced way.
Modes of data collection
Main article: Survey data collectionThere are several ways of administering a survey. The choice between administration modes is influenced by several factors, including 1) costs, 2) coverage of the target population, 3) flexibility of asking questions, 4) respondents' willingness to participate and 5) response accuracy. Different methods create mode effects that change how respondents answer, and different methods have different advantages. The most common modes of administration can be summarized as:[3]
- Telephone
- Mail (post)
- Online surveys
- Personal in-home surveys
- Personal mall or street intercept survey
- Hybrids of the above.
How to write good survey questions
Main article: Questionnaire constructionGeneral rules for writing good questions are given in classical survey books.[4] A summary of these rules was made by Ten Brink (1992).[5]
- Rule 1. Use correct spelling, punctuation and grammar style .
- Rule 2. Use specific questions. For example, "did you read a newspaper yesterday?", instead of "did you read a newspaper?".
- Rule 3. Use a short introduction to question of behaviors. In this way you cannot only refresh the memory of the respondent, but also explain what you mean with the concept you are using. For example, with wines, you may not only mean red or white wine, but liqueurs, cordials, sherries, tables wines and sparkling wines.
- Rule 4. Avoid the use of technical terms and jargon. An exception to this rule are questions that are made for a specific group of respondents, who regularly use jargon, e.g., doctors, lawyers and researchers.
- Rule 5. Avoid questions that do not have a single answer. For example, "do you like to walk and ride to school?". Somebody who likes to walk, but does not like to cycle, cannot answer this question in the right way.
- Rule 6. Avoid negative phrasing, e.g., "should the school not be improved?". This can lead to confusion and cost more effort to answer the question correctly.
- Rule 7. Avoid words and expressions with multiple-meanings, like any and just.
- Rule 8. Avoid stereotyping, offensive and emotionally loaded language. See also research ethics
The importance of testing
Such rules of thumb can be useful in constructing a survey, however are not sufficient by themselves to account for all problems, which often depend on the subject matter of the survey itself. For example, reference periods or other recall requirements may be more difficult to accurately recall than anticipated, the design of the survey may cause sequencing errors or omissions, or order effects may occur between questions or within response options (such as primacy or recency effects), and mode effects may occur if multiple modes are used (such as self-complete administration for some respondents and verbal or computer-based for others).
To avoid these problems, survey researchers test their survey on potential respondents from the target population prior to full-scale administration. This can be done in a number of ways, such as by administering the survey as intended, and informally interviewing or debriefing respondents afterward. More systematic approaches involve error analysis of self-complete forms, cognitive interviews to understand the mental process respondents use to generate answers, usability testing to ensure a form is usable (regardless of the validity of questions). Testing with potential respondents can also re-confirm prior decisions about the content of the survey instrument, gathering further evidence for content validity. Expert reviews are also used, where draft survey instruments are shared with other experts or colleagues, however should not replace testing with respondents.
Such non-experimental testing methods can give an indication of problems, however can not unquestionably determine the source of a problem. Therefore in some cases, experiments are used to determine the causal effects of a problem.
Response formats
Usually, a survey consists of a number of questions that the respondent has to answer in a set format. A distinction is made between open-ended and closed-ended questions. An open-ended question asks the respondent to formulate his own answer, whereas a closed-ended question has the respondent pick an answer from a given number of options. The response options for a closed-ended question should be exhaustive and mutually exclusive. Four types of response scales for closed-ended questions are distinguished:
- Dichotomous, where the respondent has two options
- Nominal-polytomous, where the respondent has more than two unordered options
- Ordinal-polytomous, where the respondent has more than two ordered options
- (bounded)Continuous, where the respondent is presented with a continuous scale
A respondent's answer to an open-ended question can be coded into a response scale afterwards,[3] or analysed using more qualitative methods.
Advantages and disadvantages of surveys
Advantages
- They are relatively easy to administer.
- Can be developed in less time compared with other data-collection methods.
- Can be cost-effective.
- Few 'experts' are required to develop a survey, which may will increase the reliability of the survey data.
- If conducted remotely, can reduce or obviate geographical dependence.
- Useful in describing the characteristics of a large population assuming the sampling is valid.
- Can be administered remotely via the Web, mobile devices, mail, e-mail, telephone, etc.
- Efficient at collecting information from a large number of respondents.
- Statistical techniques can be applied to the survey data to determine validity, reliability, and statistical significance even when analyzing multiple variables.
- Many questions can be asked about a given topic giving considerable flexibility to the analysis.
- Support both between and within-subjects study designs.
- A wide range of information can be collected (e.g., attitudes, values, beliefs, and behaviour).
- Because they are standardized, they are relatively free from several types of errors.
Disadvantages
The reliability of survey data may depend on the following:
- Respondents' motivation, honesty, memory, and ability to respond:
- Respondents may not be motivated to give accurate answers.
- Respondents may be motivated to give answers that present themselves in a favorable light.
- Respondents may not be fully aware of their reasons for any given action.
- Structured surveys, particularly those with closed ended questions, may have low validity when researching affective variables.
- Self-selection bias. Although the individuals chosen to participate in surveys are often randomly sampled, errors due to non-response may exist (see also chapter 13 of Adér et al. (2008) for more information on how to deal with non-responders and biased data). That is, people who choose to respond on the survey may be different from those who do not respond, thus biasing the estimates. For example, polls or surveys that are conducted by calling a random sample of publicly available telephone numbers will not include the responses of people with unlisted telephone numbers, mobile (cell) phone numbers, people who are unable to answer the phone (e.g., because they normally sleep during the time of day the survey is conducted, because they are at work, etc.), people who do not answer calls from unknown or unfamiliar telephone numbers. Likewise, such a survey will include a disproportionate number of respondents who have traditional, land-line telephone service with listed phone numbers, and people who stay home much of the day and are much more likely to be available to participate in the survey (e.g., people who are unemployed, disabled, elderly, etc.).
- Question design. Survey question answer-choices could lead to vague data sets because at times they are relative only to a personal abstract notion concerning "strength of choice". For instance the choice "moderately agree" may mean different things to different subjects, and to anyone interpreting the data for correlation. Even 'yes' or 'no' answers are problematic because subjects may for instance put "no" if the choice "only once" is not available.
Nonresponse reduction
The following ways have been recommended for reducing nonresponse in telephone and face-to-face surveys:[4]
- Advance letter. A short letter is sent in advance to inform the sampled respondents about the upcoming survey. The style of the letter should be personalized but not overdone. First, it announces that a phone call will be made/ or an interviewer wants to make an appointment to do the survey face-to-face. Second, the research topic will be described. Last, it allows both an expression of the surveyor's appreciation of cooperation and an opening to ask questions on the survey.
- Training. The interviewers are thoroughly trained in how to ask respondents questions, how to work with computers and making schedules for callbacks to respondents who were not reached.
- Short introduction. The interviewer should always start with a short instruction about him or herself. She/he should give her name, the institute she is working for, the length of the interview and goal of the interview. Also it can be useful to make clear that you are not selling anything: this has been shown to lead led to a slightly higher responding rate.[6]
- Respondent-friendly survey questionnaire. The questions asked must be clear, non-offensive and easy to respond to for the subjects under study.
Other methods to increase response rates
- brevity – single page if possible
- financial incentives
- paid in advance
- paid at completion
- non-monetary incentives
- commodity giveaways (pens, notepads)
- entry into a lottery, draw or contest
- discount coupons
- promise of contribution to charity
- preliminary notification
- foot-in-the-door techniques – start with a small inconsequential request
- personalization of the request – address specific individuals
- follow-up requests – multiple requests
- emotional appeals
- bids for sympathy
- convince respondent that they can make a difference
- guarantee anonymity
- legal compulsion (certain government-run surveys)
Interviewer effects
Survey methodologists have devoted much effort to determine the extent to which interviewee responses are affected by physical characteristics of the interviewer. Main interviewer traits that have been demonstrated to influence survey responses are race [7] , gender [8] and relative body weight (BMI) .[9] These interviewer effects are particularly operant when questions are related to the interviewer trait. Hence, race of interviewer has been shown to affect responses to measures regarding racial attitudes ,[10] interviewer sex responses to questions involving gender issues ,[11] and interviewer BMI answers to eating and dieting-related questions .[12] While interviewer effects have been investigated mainly for face-to-face surveys, they have also been shown to exist for interview modes with no visual contact, such as telephone surveys and in video-enhanced web surveys. The explanation typically provided for interviewer effects is that of social desirability. Survey participants may attempt to project a positive self-image in an effort to conform to the norms they attribute to the interviewer asking questions.
See also
| Statistics portal |
| Wikiversity has learning materials about Questionnaire |
- Data Documentation Initiative
- Enterprise feedback management (EFM)
- Likert Scale
- Official statistics
- Paid survey
- Quantitative marketing research
- Questionnaire construction
- Social research
| This article includes a list of references, but its sources remain unclear because it has insufficient inline citations. Please help to improve this article by introducing more precise citations. (April 2009) |
Notes
- ^ http://whatisasurvey.info/
- ^ a b Groves, R.M.; Fowler, F. J.; Couper, M.P.; Lepkowski, J.M.; Singer, E.; Tourangeau, R. (2009). Survey Methodology. New Jersey: John Wiley & Sons. ISBN 978-1-118-21134-2.
- ^ a b Mellenbergh, G.J. (2008). Chapter 9: Surveys. In H.J. Adèr & G.J. Mellenbergh (Eds.) (with contributions by D.J. Hand), Advising on Research Methods: A consultant's companion (pp. 183–209). Huizen, The Netherlands: Johannes van Kessel Publishing.
- ^ a b Dillman, D.A. (1978) Mail and telephone surveys: The total design method. Wiley. ISBN 0-471-21555-4
- ^ Ten Brink (1992). Het schrijven van vragen[item writing]. Unpublished master's thesis, Vakgroep Psychologische Methodenleer, Department of Psychology,University of Amsterdam, the Netherlands.
- ^ De Leeuw, E.D. (2001). "I am not selling anything: Experiments in telephone introductions". Kwantitatieve Methoden, 22, 41–48.
- ^ Hill, M.E (2002). "Race of the interviewer and perception of skin color: Evidence from the multi-city study of urban inequality". American Sociological Review 67 (1): 99–108. http://www.jstor.org/stable/3088935.
- ^ Flores-Macias, F.; Lawson, C. (2008). "Effects of interviewer gender on survey responses: Findings from a household survey in Mexico". International Journal of Public Opinion Research 20 (1): 100–110. doi:10.1093/ijpor/edn007.
- ^ Eisinga, R.; Te Grotenhuis, M.; Larsen, J.K.; Pelzer, B.; Van Strien, T. (2011). "BMI of interviewer effects". International Journal of Public Opinion Research 23 (4): 530–543. doi:10.1093/ijpor/edr026.
- ^ Anderson, B.A.; Abramson, B.D. (1988). "The effects of the race of the interviewer on race-related attitudes of black respondents in SRC/CPS national election studies". Public Opinion Quarterly 52 (3): 1–28. doi:10.1086/269108.
- ^ Kane, E.W.; Macaulay, L.J. (1993). "Interviewer gender and gender attitudes". Public Opinion Quarterly 57 (1): 1–28. doi:10.1086/269352.
- ^ Eisinga, R.; Te Grotenhuis, M.; Larsen, J.K.; Pelzer, B.. "Interviewer BMI effects on under- and over-reporting of restrained eating. Evidence from a national Dutch face-to-face survey and a postal follow-up". International Journal of Public Health. doi:10.1007/s00038-011-0323-z.
References
- Abramson, J.J. and Abramson, Z.H. (1999).Survey Methods in Community Medicine: Epidemiological Research, Programme Evaluation, Clinical Trials (5th edition). London: Churchill Livingstone/Elsevier Health Sciences ISBN 0-443-06163-7
- Groves, R.M. (1989). Survey Errors and Survey Costs Wiley. ISBN 0-471-61171-9
- Ornstein, M.D. (1998). "Survey Research." Current Sociology 46(4): iii-136.
- Shaughnessy, J. J., Zechmeister, E. B., & Zechmeister, J. S. (2006). Research Methods in Psychology (Seventh Edition ed.). McGraw–Hill Higher Education. ISBN 0-07-111655-9 (pp. 143–192)
- Adèr, H. J., Mellenbergh, G. J., & Hand, D. J. (2008). Advising on research methods: A consultant's companion. Huizen, The Netherlands: Johannes van Kessel Publishing.
- Dillman, D.A. (1978) Mail and telephone surveys: The total design method. New York: Wiley. ISBN 0-471-21555-4
Further reading
- Andres, Lesley (2012). "Designing and Doing Survey Research". London: Sage.
- Leung, Wai-Ching (2001) "Conducting a Survey", in Student BMJ, (British Medical Journal, Student Edition), May 2001
External links
- Surveys at the Open Directory Project
- OmniPHP(tm) SurveyEngine – An open source advanced survey development application that allows creating any type of web-based survey.
- Nonprofit Research Collection on the Use of Surveys in Nonprofit Research Published on IssueLab
- Survey Question Bank
- Designing surveys – a basic guide
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Categories:
- Survey methodology
- Marketing
- Market research
- Psychometrics
- Research methods
- Quantitative research
- Evaluation methods
- Data collection
- Sampling (statistics)
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