Editing Sampling (statistics) (section)

===Non-sampling error===
{{main|Non-sampling error}}
Non-sampling errors are other errors which can impact final survey estimates, caused by problems in data collection, processing, or sample design. Such errors may include:
# Over-coverage: inclusion of data from outside of the population
# Under-coverage: sampling frame does not include elements in the population.
# Measurement error: e.g. when respondents misunderstand a question, or find it difficult to answer
# Processing error: mistakes in data coding
# [[Participation bias|Non-response or Participation bias]]: failure to obtain complete data from all selected individuals
After sampling, a review is held of the exact process followed in sampling, rather than that intended, in order to study any effects that any divergences might have on subsequent analysis.

A particular problem involves ''non-response''. Two major types of non-response exist:<ref>Berinsky, A. J. (2008). "Survey non-response". In: W. Donsbach & M. W. Traugott (Eds.), ''The Sage handbook of public opinion research'' (pp. 309–321). Thousand Oaks, CA: Sage Publications.</ref><ref name="Dillman et al 2002">Dillman, D. A., Eltinge, J. L., Groves, R. M., & Little, R. J. A. (2002). "Survey nonresponse in design, data collection, and analysis". In: R. M. Groves, D. A. Dillman, J. L. Eltinge, & R. J. A. Little (Eds.), ''Survey nonresponse'' (pp. 3–26). New York: John Wiley & Sons.</ref>
* unit nonresponse (lack of completion of any part of the survey)
* item non-response (submission or participation in survey but failing to complete one or more components/questions of the survey)

In [[survey sampling]], many of the individuals identified as part of the sample may be unwilling to participate, not have the time to participate ([[opportunity cost]]),<ref>Dillman, D.A., Smyth, J.D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys: The tailored design method. San Francisco: Jossey-Bass.</ref> or survey administrators may not have been able to contact them. In this case, there is a risk of differences between respondents and nonrespondents, leading to biased estimates of population parameters. This is often addressed by improving survey design, offering incentives, and conducting follow-up studies which make a repeated attempt to contact the unresponsive and to characterize their similarities and differences with the rest of the frame.<ref>Vehovar, V., Batagelj, Z., Manfreda, K.L., & Zaletel, M. (2002). "Nonresponse in web surveys". In: R. M. Groves, D. A. Dillman, J. L. Eltinge, & R. J. A. Little (Eds.), ''Survey nonresponse'' (pp. 229–242). New York: John Wiley & Sons.</ref> The effects can also be mitigated by weighting the data (when population benchmarks are available) or by imputing data based on answers to other questions. Nonresponse is particularly a problem in internet sampling. Reasons for this problem may include improperly designed surveys,<ref name="Dillman et al 2002"/> over-surveying (or survey fatigue),<ref name="SM"/><ref>
{{cite book
 | last1 = Porter
 | last2 = Whitcomb
 | last3 = Weitzer
 | chapter = Multiple surveys of students and survey fatigue
 | editor1-last = Porter
 | editor1-first = Stephen R
 | title = Overcoming survey research problems
 | url = https://books.google.com/books?id=9TadAAAAMAAJ
 | series = New directions for institutional research
 | issue = 121
 | location = San Francisco
 | publisher = Jossey-Bass
 | date = 2004
 | pages = 63–74
 | isbn = 9780787974770
 | access-date = 15 July 2019
}}
</ref>{{request quotation|date=July 2019}}
and the fact that potential participants may have multiple e-mail addresses, which they do not use anymore or do not check regularly.