Statistical survey

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Statistical surveys are used to collect quantitative information about items in a population. Surveys of human populations and institutions are common in political polling and government, health, social science and marketing research. A survey may focus on opinions or factual information depending on its purpose, and many surveys involve administering questions to individuals. When the questions are administered by a researcher, the survey is called a structured interview or a researcher-administered survey. When the questions are administered by the respondent, the survey is referred to as a questionnaire or a self-administered survey.

[edit] Structure and standardization

The questions are usually structured and standardized. The structure is intended to reduce bias; (see questionnaire construction). For example, questions should be ordered in such a way that a question does not influence the response to subsequent questions. Surveys are standardized to ensure reliability, generalizability, and validity (see quantitative marketing research). Every respondent should be presented with the same questions and in the same order as other respondents.

In organizational development (OD), carefully constructed survey instruments are often used as the basis for data gathering, organizational diagnosis, and subsequent action planning. Some OD practitioners (e.g. Fred Nickols) even consider survey guided development as the sine qua non of OD.

[edit] Serial surveys

Serial surveys are those which repeat the same questions at different points in time, producing time-series data. They typically fall into two types:

Cross-sectional surveys which draw a new sample each time. In a sense any one-off survey will also be cross-sectional.
Longitudinal surveys where the sample from the initial survey is recontacted at a later date to be asked the same questions.

[edit] Advantages and disadvantages of surveys

[edit] Advantages

It is an efficient way of collecting information from a large number of respondents. Very large samples are possible. Statistical techniques can be used to determine validity, reliability, and statistical significance.
Surveys are flexible in the sense that a wide range of information can be collected. They can be used to study attitudes, values, beliefs, and past behaviors.
Because they are standardized, they are relatively free from several types of errors.
They are relatively easy to administer.
There is an economy in data collection due to the focus provided by standardized questions. Only questions of interest to the researcher are asked, recorded, codified, and analyzed. Time and money is not spent on tangential questions.

[edit] Disadvantages

They depend on subjects’ motivation, honesty, memory, and ability to respond. Subjects may not be aware of their reasons for any given action. They may have forgotten their reasons. They may not be motivated to give accurate answers, in fact, they may be motivated to give answers that present themselves in a favorable light.
Structured surveys, particularly those with closed ended questions, may have low validity when researching affective variables.
Although the chosen survey individuals are often a random sample, errors due to nonresponse may exist. That is, people who choose to respond on the survey may be different from those who do not respond, thus biasing the estimates.
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.

[edit] Characteristics of researcher-administered surveys

Fewer misunderstood questions and inappropriate responses.
Fewer incomplete responses.
Generally higher response rates and better information on nonresponse, but...
Respondents may be unwilling to discuss sensitive topics with a stranger.
Greater control over the environment that the survey is administered in.
Additional information can be collected from respondent.
Subject to interviewer bias (e.g. answers influenced by desire to impress interviewer).
Generally expensive/time-consuming to run.

[edit] Characteristics of self-administered surveys

Respondents are more likely to stop participating mid-way through the survey (drop-offs).
Respondents cannot ask for clarification.
Low response rate in some modes.
Often respondents returning survey represent extremes of the population - skewed responses (consequence of low response rates).
Allows shy respondents to answer sensitive questions in private.
No interviewer intervention available for probing or explanation.
Respondents can read the whole questionnaire before answering any questions.
Free of interviewer bias.

[edit] Questions and 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 respondents answer to an open-ended question is coded into a response scale afterwards.

[edit] Modes of Data Collection

There are several ways of administering a survey, including:

[edit] Telephone

use of interviewers encourages sample persons to respond, leading to higher response rates.^[1]
interviewers can increase comprehension of questions by answering respondents' questions.
fairly cost efficient, depending on local call charge structure
good for large national (or international) sampling frames
some potential for interviewer bias (e.g. some people may be more willing to discuss a sensitive issue with a female interviewer than with a male one)
cannot be used for non-audio information (graphics, demonstrations, taste/smell samples)
three types:
- traditional telephone interviews
- computer assisted telephone dialing
- computer assisted telephone interviewing (CATI)

[edit] Mail

the questionnaire may be handed to the respondents or mailed to them, but in all cases they are returned to the researcher via mail.
cost is very low, since bulk postage is cheap in most countries
long time delays, often several months, before the surveys are returned and statistical analysis can begin
not suitable for issues that may require clarification
respondents can answer at their own convenience (allowing them to break up long surveys; also useful if they need to check records to answer a question)
no interviewer bias introduced
large amount of information can be obtained: some mail surveys are as long as 50 pages
response rates can be improved by using mail panels
- members of the panel have agreed to participate
- panels can be used in longitudinal designs where the same respondents are surveyed several

[edit] Online surveys

can use web or e-mail
- web is preferred over e-mail because interactive HTML forms can be used
often inexpensive to administer
very fast results
easy to modify
response rates can be improved by using Online panels - members of the panel have agreed to participate
if not password-protected, easy to manipulate by completing multiple times to skew results
data creation, manipulation and reporting can be automated and/or easily exported into a format which can be read by PSPP, DAP or other statistical analysis software
data sets created in real time
some are incentive based (such as Survey Vault or YouGov)
may skew sample towards a younger demographic compared with CATI
often difficult to determine/control selection probabilities, hindering quantitative analysis of data

[edit] Personal in-home survey

respondents are interviewed in person, in their homes (or at the front door)
very high cost
suitable when graphic representations, smells, or demonstrations are involved
often suitable for long surveys (but some respondents object to allowing strangers into their home for extended periods)
suitable for locations where telephone or mail are not developed
skilled interviewers can persuade respondents to cooperate, improving response rates
potential for interviewer bias
increasing use of computer-assisted personal interviewing (CAPI) to streamline data collection/processing and guide sequencing of complex surveys

[edit] Personal mall intercept survey

shoppers at malls are intercepted - they are either interviewed on the spot, taken to a room and interviewed, or taken to a room and given a self-administered questionnaire
socially acceptable - people feel that a mall is a more appropriate place to do research than their home
potential for interviewer bias
fast
easy to manipulate by completing multiple times to skew results

[edit] Methods used 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
claimed affiliation with universities, research institutions, or charities
emotional appeals
bids for sympathy
convince respondent that they can make a difference
guarantee anonymity
legal compulsion (certain government-run surveys)

[edit] Sampling

Main article: Sampling (statistics)

Sample selection is critical to the validity of the information that represents the populations that are being studied. The approach of the sampling helps to determine the focus of the study and allows better acceptance of the generalizations that are being made. Careful use of biased sampling can be used if it is justified and as long as it is noted that the resulting sample may not be a true representation of the population of the study. There are two different approaches to sampling in survey research:

There is nonprobability sampling approach. In this approach the researcher does not know each element's probability of selection in the sample. The most commonly used nonprobability sampling method is the convenience sampling approach. With this method, it only samples those who are available and willing to participate in the survey. The use of this approach allows for convenience for the researcher while possibly losing data validity due to the lack of representation.
The probability sampling approach for research methods gives each element a known chance of being included in the sample. This method is closer to a true representation of the population. It can be difficult to use due to cost of a rigorous sampling method, and difficulty in obtaining full coverage of the target population, but the generalizations that come from it are more likely to be closer to a true representation of the population. Different forms of probability sampling are designed to achieve various benefits - e.g. theoretical simplicity, operational simplicity, detailed information on subpopulations, or minimal cost. Some common forms:

- Equal probability of selection designs (EPS), in which each element of the population has an equal chance of being included in the sample. This uniformity makes EPS surveys relatively simple to interpret. Forms of EPS include Simple random sampling (SRS) and systematic sampling.

- Probability-proportional-to-size designs (PPS), in which 'larger' elements (according to some known measure of size) have a higher chance of selection. This approach is common in business surveys where the object is to determine sector totals (e.g. "total employment in manufacturing sectors"); compared to EPS, concentrating on larger elements may produce better accuracy for the same cost/sample size.

- Stratified random sampling approach, in which the population is divided into subpopulations (called strata) and random samples are then drawn separately from each of these strata, using any probability sampling method (sometimes including further sub-stratification). This may be done to provide better control over the sample size (and hence, accuracy) within each subpopulation; when the variable/s of interest are correlated with subpopulation, it can also improve overall accuracy. Another use for stratification is when different subpopulations require different sampling methods - for instance, a business survey might use EPS for businesses whose 'size' is not known and PPS elsewhere.

[edit] Survey Methodology and Research Institutes

[edit] See also

Statistics portal

[edit] Lists of related topics

[edit] References

Abramson, J.J. and Abramson, Z.H. 1999. "Survey Methods in Community Medicine: Epidemiological Research, Programme Evaluation, Clincal Trials" (5th edition). London: Churchill Livingstone.

Groves, R.M. 1989. Survey Errors and Survey Costs. New York: Wiley.

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., pp. 143–192). New York, New York: Higher Education.

^ Groves, R.M. (1989) Survey Costs and Survey Errors. New York: Wiley.

[edit] Further reading

Leung, Wai-Ching, "Conducting a Survey", in Student BMJ, (British Medical Journal, Student Edition), May 2001

[edit] External links

Surveys at the Open Directory Project

[0] Groves, R.M. (1989) Survey Costs and Survey Errors. New York: Wiley.

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